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10 merged results for "Crash Prediction Models"

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. Jointly predicting secondary crash occurrence and spatiotemporal location via generative adversarial networks under data imbalance.

    Chen J, Li Y, Ling C, Liu P · 2026 · Accident; analysis and prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.aap.2026.108744

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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
  2. Causal analysis from primary crashes to secondary crashes on freeways using an integrated Bayesian and path exploration framework.

    Gong X, Tang J, Liu R, Lou B · 2026 · Accident; analysis and prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.aap.2026.108770

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  3. Factors influencing motorcycle crash risk and accident prediction ability: The role of hazard perception training in Thailand.

    Inmor T, Kanitpong K · 2026 · Accident; analysis and prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.aap.2026.108771

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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
  4. DKD-MARL: a data-knowledge dual-driven multi-agent reinforcement learning framework for traffic crash severity prediction.

    Zhang J, Dai S, Zhao D, Sovetbekov B · 2026 · Accident; analysis and prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.aap.2026.108775

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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
  5. Geometry-informed Bayesian deep learning for proactive driving risk assessment: a full spatiotemporal probabilistic risk field approach.

    Hu Z, Zhu F, Ming X, Meng X · 2026 · Accident; analysis and prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.aap.2026.108783

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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
  6. Contributing factors to the severity of crash injury and vehicle damage involving Japanese lightweight vehicles (K-car): Considering unobserved heterogeneity.

    Wang L, Lee JJ, Hu J, Mao S · 2026 · Journal of safety research

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.jsr.2026.05.017

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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
  7. Quantification of buttocks and thigh deformation in seating: a multi-modality approach.

    Mischo SH, Wolf J, Brandt KM, von Kleeck W · 2026 · Traffic injury prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1080/15389588.2026.2713754

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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
  8. Tissue-level distal tibia simulations to assess strain as a predictor of AIS 2 ankle injuries.

    Noss J, Iyer R, Holcombe S, Hallman J · 2026 · Traffic injury prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1080/15389588.2026.2717384

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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. Two‑tier prediction framework with OR‑voting for real‑time freeway secondary-crash prediction: Balancing sensitivity and specificity.

    Wu X, Guo J, Li H, Yang Y · 2026 · Traffic injury prevention

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1080/15389588.2026.2720902

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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
  10. Correlates of unsafe driving in non-professional drivers: insights from a data-driven modeling approach.

    Abdolrazaghi A, Mirzahossein H · 2026 · The Journal of the Egyptian Public Health Association

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.1186/s42506-026-00234-1

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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