{"id":"W2160093842","doi":"10.1136/ip.2006.013326","title":"From targeted “black spots” to area-wide pedestrian safety","year":2006,"lang":"en","type":"article","venue":"Injury Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Sante Montreal; Institut National de Santé Publique du Québec","funders":"","keywords":"Pedestrian; Black spot; Forensic engineering; Poison control; Transport engineering; Engineering; Spots; Medical emergency; Medicine; Biology","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":[0.0008055987,0.0004360999,0.0002050724,0.003251519,0.0007554531,0.00123631,0.0005456972,0.0002913009,0.002933501],"category_scores_gemma":[0.003661631,0.0001976912,0.0002040589,0.003532904,0.0009236024,0.001012231,0.001416321,0.000217019,0.0003248717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002160714,"about_ca_system_score_gemma":0.001687555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1909246,"about_ca_topic_score_gemma":0.3094808,"domain_scores_codex":[0.9991167,0.0002088043,0.00003238457,0.0001863582,0.0002974462,0.0001583695],"domain_scores_gemma":[0.9977691,0.0002979793,0.0008457129,0.000149149,0.0007975961,0.0001404944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002921448,0.00003572263,0.9140887,0.0002478393,0.0000920376,0.0009345129,0.003265724,0.003999669,0.001494435,0.002223828,0.003190676,0.07013471],"study_design_scores_gemma":[0.00001386579,0.0001903303,0.9776933,0.0001481294,0.00007670635,0.001104632,0.0048911,0.005025337,0.001150634,0.001855517,0.00782116,0.00002924106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847087,0.0008621314,0.00510543,0.0003314902,0.0000109263,0.00008886721,0.001303307,0.00006982867,0.007519418],"genre_scores_gemma":[0.9975822,0.0002034599,0.001188595,0.00004157573,0.000005619943,0.00002466534,0.0003372307,0.00000553851,0.0006110817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1909246,"threshold_uncertainty_score":0.3796266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00653778545385191,"score_gpt":0.2164660810945706,"score_spread":0.2099282956407187,"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."}}