{"id":"W2767986748","doi":"10.4271/wp-0005","title":"PROACTIVE METHODS FOR ROAD SAFETY ANALYSIS","year":2017,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Crash; Scope (computer science); Metric (unit); Computer science; Risk analysis (engineering); Identification (biology); Safety case; Transport engineering; Engineering; Business; Operations management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.004685303,0.001529925,0.001011851,0.002163571,0.0007387094,0.003329603,0.002322259,0.001390853,0.007353988],"category_scores_gemma":[0.01007911,0.0007697109,0.001515649,0.001931864,0.00174026,0.003015818,0.003291524,0.003219563,0.003485426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443104,"about_ca_system_score_gemma":0.001882925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002366155,"about_ca_topic_score_gemma":0.002308547,"domain_scores_codex":[0.9961402,0.001643356,0.0001749004,0.0005353833,0.001400547,0.0001056081],"domain_scores_gemma":[0.9947923,0.00288809,0.0003234658,0.00105933,0.0008361805,0.000100623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005670321,0.000105169,0.001073475,0.0006471709,0.0002020625,0.00008953506,0.0003040262,0.09298535,0.003208488,0.4934078,0.02194858,0.3859716],"study_design_scores_gemma":[0.00002275299,0.00005332056,0.0004825597,0.0002319218,0.0000486974,0.0001085202,0.0001069328,0.4260222,0.001753377,0.5019495,0.0691684,0.00005180777],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005492763,0.002309749,0.9885405,0.0005941021,0.0002165949,0.00006296183,0.0001010104,0.0006646934,0.006961252],"genre_scores_gemma":[0.07983664,0.005528846,0.8961944,0.0007303797,0.0008215561,0.0005467358,0.0005263788,0.0004790301,0.01533607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007353988,"threshold_uncertainty_score":0.02477854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792859553994067,"score_gpt":0.3089133228680183,"score_spread":0.2909847273280777,"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."}}