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54 merged results for "Deep Learning Applications"

Partial results: at least one source did not answer. Available results are shown rather than treating an upstream outage as zero matches.

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  1. Machine Learning–Based Wear Prediction of Recycled Magnesium Matrix Composites Reinforced With Ceramic Fibers

    Meenakshi Sudarvizhi Seenipeyathevar, Prasath Palaniappan, Vijayakumar Arumugam, Vivek Sivakumar · 2026 · Engineering Reports

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.1002/eng2.70686

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  2. Advancements in 7T magnetic resonance diffusion imaging: Technological innovations and applications in neuroimaging

    Lisha Nie, Siyi Li, Bing Wu, Yuhui Xiong · 2024 · iRADIOLOGY

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.1002/ird3.92

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  3. Capacity Requirements Planning for Production Companies Using Deep Reinforcement Learning

    Harald Schallner · 2019

    uncertain Transparent signal score 51/100 · policy 1.0.0

    Found in hal · DOI 10.1007/978-3-030-19823-7_21

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  4. Comparative Performance Study on Human Activity Recognition with Deep Neural Networks

    Kavya Sree Gajjala, Ashika Kothamachu Ramesh, Kotaro Nakano, Basabi Chakraborty · 2021

    uncertain Transparent signal score 51/100 · policy 1.0.0

    Found in hal · DOI 10.1007/978-3-030-74826-5_21

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  5. Advances in Deep Learning, Artificial Intelligence and Robotics

    Luigi Troiano, Alfredo Vaccaro, Roberto Tagliaferri, Nishtha Kesswani · 2021

    limited evidence Transparent signal score 49/100 · policy 1.0.0

    Found in hal · DOI 10.1007/978-3-030-85365-5

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  6. Machine Learning Applications in Real Estate: Critical Review of Recent Development

    Jamal Al-Qawasmi · 2022

    uncertain Transparent signal score 51/100 · policy 1.0.0

    Found in hal · DOI 10.1007/978-3-031-08337-2_20

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  7. Evaluating Augmented Reality, Deep Learning and Paper-Based Assistance Systems in Industrial Manual Assembly

    Alexander Riedel, Johanna Gerlach, Maximilian Dietsch, Frank Engelmann · 2023

    uncertain Transparent signal score 51/100 · policy 1.0.0

    Found in hal · DOI 10.1007/978-3-031-43662-8_30

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
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    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  8. A review of deep learning applications on histopathologic and genomic data in focal segmental glomerulosclerosis.

    Srikar D, Dhimole VK, Reddy SS, Gantayat SS. · 2026 · Comput Biol Chem

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1016/j.compbiolchem.2026.109517

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  9. LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles

    Yong Wang, Hongwen He, Yuankai Wu, Pei Wang · 2025 · Engineering

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.1016/j.eng.2024.10.021

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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  10. Feature-driven static analysis for learning-based android malware detection: A review

    Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour · 2026 · ICT Express

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.1016/j.icte.2026.01.005

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    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
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    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  11. Machine learning in semen analysis for male infertility: A systematic review and future directions.

    Varzaneh ZA, Khoshkangini R, Saeedi-Boroujeni A, Kazemi-Arpanahi H · 2026 · International journal of medical informatics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.ijmedinf.2026.106766

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    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  12. TTA-MVUM: A Tumor and Text-Aware Multi-View Mamba Framework for Clinical Target Volume Auto-Segmentation in Nasopharyngeal Carcinoma Radiotherapy.

    Ma X, Wu R, Yi J, Dai J · 2026 · International journal of radiation oncology, biology, physics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.ijrobp.2026.10.035

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  13. A survey of multimodal hybrid deep learning for computer vision: Architectures, applications, trends, and challenges

    Khaled Bayoudh · 2024 · Information Fusion

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in hal · DOI 10.1016/j.inffus.2023.102217

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  14. Deep learning applications in cancer treatment Prediction: Comprehensive research foundation for systematic review and Meta-Analysis.

    Tunca S, Balcioglu YS, Elmas-Cecen BO. · 2026 · J Biomed Inform

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1016/j.jbi.2026.105068

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  15. Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: Applications to a large-scale, clinically heterogeneous dataset.

    van Lune J, Mandija S, van der Heide O, Maspero M · 2027 · Med Image Anal

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1016/j.media.2026.104295

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  16. Standardising ocular surface photography for artificial intelligence: current limitations and a proposed roadmap.

    Romano V, Steger B, Airaldi M, Giuliano F · 2026 · Progress in retinal and eye research

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.preteyeres.2026.101539

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  17. One step beyond CASA Systems: Artificial intelligence (AI) and deep learning (DL) for canine sperm analysis (CSA).

    Cagin Ari U · 2026 · Theriogenology

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.theriogenology.2026.118309

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  18. SeqSol-FECS: An Integrated Deep Learning and Structural Modeling Framework for Protein Solubility Engineering.

    Guo Q, Zhou XT, Zhou R, Fang ZR · 2026 · Biomacromolecules

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1021/acs.biomac.6c01393

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  19. Machine Learning Predictions of Experimental Mössbauer Properties of Fe-Containing Molecular Complexes and Protein Models.

    Skoulidas I, Tavasolikejani S, Morgan D, Chu JM · 2026 · Journal of chemical information and modeling

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1021/acs.jcim.6c02183

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  20. Deep-Learning-Empowered Gold Nanoparticle Dimer-Assisted Hyperbolic Metamaterial Surface Plasmon Resonance Fiber-Optic Sensor for Ultrasensitive Mercury Ion Detection.

    Li L, Zhao X, Hang B, Yu S · 2026 · ACS applied materials & interfaces

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1021/acsami.6c19051

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  21. Exploration and performance analysis of deep learning applications in spermatic vein ultrasound segmentation.

    Hu Y, Zou P, Yan R, Zeng X · 2026 · Biomed Phys Eng Express

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1088/2057-1976/ae4eed

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  22. A comprehensive review of deep learning applications in the segmentation and classification of skin cancer.

    Saleh N, Shaaban AR, Salaheldin AM. · 2026 · Biomed Phys Eng Express

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1088/2057-1976/ae74d6

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  23. An overview of self-supervised deep learning applications to molecular data.

    Borràs Ferrís L, Fratti R, Nucera V, Oreiller V · 2026 · Brief Bioinform

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1093/bib/bbag380

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  24. Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

    Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno, Antonio Brunetti · 2023 · IEEE Access

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.1109/access.2023.3271748

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 4 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  25. Semi-Dynamic Ensemble for Evolutionary NAS in Continual Learning

    Daniel Victor Ferreira, Lucas Rakotoarivony, Agathe Archet · 2025

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in hal · DOI 10.1109/icprs66293.2025.11302835

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  26. Advanced Two-Stage Authentication with EEG: Inter-Subject P300 ERP Classification Using EEGNet for User Recognition.

    Khalil AEK, Antelis JM, Cantoral-Ceballos JA, Diaz JAP · 2026 · IEEE journal of biomedical and health informatics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1109/jbhi.2026.3747896

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  27. Optical Switching for data centers and advanced computing systems

    Patronas, Giannis, Terzenidis, Nikos, Kashinkunti, Prethvi, Zahavi, Eitan · 2024

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.1364/jocn.534317

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  28. Deep learning applications in parasite microscopy: A scoping review.

    Maniraj RM, Osman E, Sheikh Abdullah SNH, Azil AH · 2026 · PLoS Negl Trop Dis

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1371/journal.pntd.0014774

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  29. Deep learning applications in osteosarcoma MRI: A systematic review of recent advances in AI-based osteosarcoma diagnosis.

    Himel GMS, Achuthan A, Mohamed YA, Khoo BE · 2026 · PLoS One

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.1371/journal.pone.0354896

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  30. PancreaGuide for Computed Tomography Report Interpretation and Perioperative Consultation in Pancreatic Cancer: Development and Retrospective Evaluation of a Knowledge-Augmented Large Language Model Agent.

    Kuang T, Wang R, Zhang S, Sun Y · 2026 · Journal of medical Internet research

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.2196/101607

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  31. Unsupervised Deep Anomaly Detection for Industrial Multivariate Time Series Data

    Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang · 2024 · Applied Sciences

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.3390/app14020774

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  32. Convergence of Artificial Intelligence and Wearables in Strength Training and Performance Monitoring: A Scoping Review

    Eleftherios Fyntikakis, Spyridon Plakias, Themistoklis Tsatalas, Minas A. Mina · 2026 · Applied Sciences

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.3390/app16073565

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  33. Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks

    Natasha Dropka, Stefan Ecklebe, Martin Holena · 2021 · Crystals

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.3390/cryst11020138

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  34. HIFU Tissue Degeneration Classification Based on Multifractal Detrending Fluctuation Analysis and Vision Transformer

    Hu Dong, Xin Tong, Gang Liu · 2026 · Fractal and Fractional

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.3390/fractalfract10090609

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  35. Artificial Intelligence for Neonatal and Perinatal Mortality Prevention: A Systematic Review of Machine Learning and Deep Learning Applications.

    Jiménez EG, Díaz JDM. · 2026 · Healthcare (Basel)

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in europe-pmc · DOI 10.3390/healthcare14152339

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  36. Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

    Ifiok Udoidiok, Fuhao Li, Jielun Zhang · 2025 · Information

    uncertain Transparent signal score 53/100 · policy 1.0.0

    Found in doaj · DOI 10.3390/info17010009

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  37. Artificial Intelligence Methods in Stroke Prediction: A Narrative Review.

    Al-Salman NH, Al-Ghraibah A, Harun SN · 2026 · Annals of Indian Academy of Neurology

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.4103/aian.aian_211_26

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  38. Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study

    Mohammad Mehdi Morovati, Florian Tambon, Mina Taraghi, Amin Nikanjam · 2023

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in hal · DOI 10.48550/arxiv.2310.09575

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  39. Deep Learning & Applications

    Dr. A. Dennis Ananth, Dr. S. Markkandeyan, Dr. M. Rajakumaran, Dr. B. Lakshmi · 2024

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.14063569

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  40. Deep Learning Tutorials

    Ying, Fangli · 2025

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.15362122

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  41. The Relationship Between Cardiac Adipose Tissue and Anxiety in Bariatric Patients Deep Learning Applications in Epicardial Adipose Tissue Analysis - Graph

    Academia EduSoft · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.21836912

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  42. A Survey on Deep Learning-Based Number Plate Recognition Systems in Vehicles for Real-Time Applications- Figure 1

    Risha K. P, Jude Hemanth D · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.23299340

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  43. A Survey on Deep Learning-Based Number Plate Recognition Systems in Vehicles for Real-Time Applications- Figure 2

    Risha K. P, Jude Hemanth D · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.23299400

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  44. A Survey on Deep Learning-Based Number Plate Recognition Systems in Vehicles for Real-Time Applications- Figure 3

    Risha K. P, Jude Hemanth D · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.23299430

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  45. A Survey on Deep Learning-Based Number Plate Recognition Systems in Vehicles for Real-Time Applications- Figure 4

    Risha K. P, Jude Hemanth D · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.23299493

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  46. A Survey on Deep Learning-Based Number Plate Recognition Systems in Vehicles for Real-Time Applications- Figure 5

    Risha K. P, Jude Hemanth D · 2026 · BRAIN. Broad Research in Artificial Intelligence and Neuroscience

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.23299527

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  47. Artificial Intelligence In The Food Industry: A Review Of Quality Inspection, Spoilage Prediction, Demand Forecasting And Traceability

    Galande Atharva Satish, Prof. N. G. Rokade, Prof. M. C. Kolse, Prof. S. K. Said · 2026

    limited evidence Transparent signal score 47/100 · policy 1.0.0

    Found in datacite, datacite, datacite, datacite · DOI 10.5281/zenodo.24096930

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingPublication license: A publication license was supplied: https://creativecommons.org/licenses/by/4.0/legalcode. Presence improves reuse transparency, not research validity. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  48. Emotion Recognition Using Artificial Intelligence: A Review Of Facial, Speech And Multimodal Affective Computing

    Kashid Aditi Eknath, ; Prof. M. C. Kolse;, Prof. S. K. Said · 2026

    limited evidence Transparent signal score 47/100 · policy 1.0.0

    Found in datacite, datacite, datacite, datacite · DOI 10.5281/zenodo.24097103

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingPublication license: A publication license was supplied: https://creativecommons.org/licenses/by/4.0/legalcode. Presence improves reuse transparency, not research validity. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  49. Deep Learning Indaba Mentorship

    Siobhan Hall · 2021

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in zenodo · DOI 10.5281/zenodo.4729344

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  50. Multi-scale window heterogeneous graph attention framework driven by deep reinforcement learning for solving distributed flexible job shop scheduling problem: Online Document

    Huang Yuhan · 2026

    limited evidence Transparent signal score 47/100 · policy 1.0.0

    Found in datacite · DOI 10.57760/sciencedb.0176f

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingPublication license: A publication license was supplied: https://creativecommons.org/licenses/by-sa/4.0/legalcode. Presence improves reuse transparency, not research validity. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  51. <b>Drainage Crossing Detection Dataset for GeoAI-Based Hydrographic Mapping</b>

    Michael Edidem, Ruopu Li, Di Wu, Banafsheh Rekabdar · 2026

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in datacite · DOI 10.6084/m9.figshare.25909453.v2

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • supportingPublication license: A publication license was supplied: https://opensource.org/licenses/MIT. Presence improves reuse transparency, not research validity. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  52. Federated Learning and Deep Learning: A New Frontier for Real-World Applications

    Sridhar K. · 2025

    limited evidence Transparent signal score 49/100 · policy 1.0.0

    Found in hal · DOI 10.9734/bpi/stda/v3/3199

    Show all credibility signals
    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  53. Artificial Neural Networks and Deep Learning: A Review of Concepts, Architectures, Advances and Applications

    Mitesh Upreti, Sanjay Mathur · 2026 · Advances in Research on Teaching

    limited evidence Transparent signal score 48/100 · policy 1.0.0

    Found in hal · no DOI

    Show all credibility signals
    • not scoredDOI registered: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredDOI resolves: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch expression of concern: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch correction: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch reinstatement: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  54. Deep learning applications in parasite microscopy: A scoping review

    Maniraj R, Osman E, Sheikh Abdullah S, Azil A · 2026 · PLoS Negl Trop Dis

    uncertain Transparent signal score 50/100 · policy 1.0.0

    Found in europe-pmc · no DOI

    Show all credibility signals
    • not scoredDOI registered: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredDOI resolves: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
    • not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch retraction: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch expression of concern: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch correction: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredRetraction Watch reinstatement: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer