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10 merged results for "International University of Business Agriculture and Technology"

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. Water quality assessment in a dense urban landscape using Statistical Analysis (SA), Artificial Intelligence (AI) and Geographic Information System (GIS).

    Hasan M, Hosna AU, Sheikh MS, Khan TA · 2026 · Environmental monitoring and assessment

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1007/s10661-026-15907-9

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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
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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
  2. Next-generation meat frying technologies: Industry 5.0-enabled strategies for ultra-low flavor loss and lipid oxidation.

    Wang Z, Zhang M, Bhandari B, Rui L · 2026 · Food research international (Ottawa, Ont.)

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.foodres.2026.120334

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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
    • 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. An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images.

    Islam M, Oishy MP, Jibon FA, Das UK · 2026 · Microvascular research

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.mvr.2026.105009

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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
  4. State-level burden of chronic respiratory diseases in the USA, 1990-2023, with forecasts to 2050: a systematic analysis for the Global Burden of Disease Study 2023.

    GBD 2023 US Chronic Respiratory Disease Collaborators · 2026 · The Lancet. Respiratory medicine

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/s2213-2600(26)00218-3

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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
  5. Global, regional, and national prevalence of second-hand smoke and attributable disease burden in 204 countries and territories, 1990-2023: a systematic analysis for the Global Burden of Disease Study 2023.

    GBD 2023 Second-hand smoke Collaborators · 2026 · The Lancet. Public health

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/s2468-2667(26)00168-4

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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
    • 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
  6. The FunAqua dataset of global fungal biodiversity in aquatic ecosystems.

    Prins V, Tedersoo L, Mikryukov V, Paiste P · 2026 · Scientific data

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1038/s41597-026-07729-8

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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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    • 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
  7. Artificial Intelligence in Nursing Care: Strategies for Addressing Implementation Challenges.

    Alrazeeni DM, Alharrasi M, Rony MKK, Biswas RK · 2026 · International nursing review

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1111/inr.70241

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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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    • 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
  8. Integrating multitrait physiological approaches to characterize salinity tolerance in bread wheat (Triticum aestivum L.) genotypes.

    Khan MM, Karim MA, Haque MM, Mia MAB · 2026 · BMC plant biology

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.1186/s12870-026-09756-4

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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
    • 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
  9. A cross-sectional study investigating the impact of dietary vitamin D intake and fortification in Jordanian adults with type 2 diabetes.

    Rababah T, Al-U'datt M, Alsaad A, Gammoh S · 2026 · Food & nutrition research

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.29219/fnr.v70.11503

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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 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
  10. From body shaping to character formation: international research progress and mechanisms of exercise training interventions for juvenile delinquency.

    Xu J, Chen H, Tian M · 2026 · Frontiers in psychology

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.3389/fpsyg.2026.1888577

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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
    • 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