{"id":"W4381193003","doi":"10.32920/23542041.v1","title":"Advancing Crash Prediction Models Based on Simulated Conflicts and Exploring Their Predictive Capabilities and Transferability","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Transferability; Crash; Transport engineering; Computer science; Variable (mathematics); Road accident; Predictive modelling; Risk analysis (engineering); Business; Engineering; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003806473,0.001056946,0.0008007407,0.0008253936,0.0003791298,0.001383822,0.001711896,0.001164613,0.001295489],"category_scores_gemma":[0.01464329,0.0007088934,0.00099904,0.0005114677,0.00053514,0.001452089,0.001093791,0.001670869,0.0002150388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158822,"about_ca_system_score_gemma":0.002306054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1134188,"about_ca_topic_score_gemma":0.05191633,"domain_scores_codex":[0.9990054,0.0005178391,0.00005967893,0.0001710185,0.0001463766,0.00009975295],"domain_scores_gemma":[0.9920135,0.005958106,0.0007107963,0.0004739876,0.0007157026,0.000127839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003048842,0.0000415402,0.003804614,0.00001112839,0.00002716339,0.0000161216,0.00002679618,0.9915125,0.0002234286,0.0004694412,0.00005909241,0.003777657],"study_design_scores_gemma":[0.000002599398,0.00001459901,0.000275068,0.000002224575,0.000003269951,0.000001573424,0.000007669036,0.9994059,0.00009767657,0.0001633368,0.00002328925,0.000002750989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7434592,0.0002662973,0.2499475,0.0006989905,0.00005134637,0.0002686759,0.0005921318,0.000801528,0.003914359],"genre_scores_gemma":[0.9789474,0.0001031862,0.02002005,0.00004401483,0.00001198242,0.00008293809,0.0001997536,0.00002704557,0.0005635795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1134188,"threshold_uncertainty_score":0.2255173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04577589050244765,"score_gpt":0.216486051204812,"score_spread":0.1707101607023643,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}