{"id":"W2682652219","doi":"10.1139/cjce-2016-0586","title":"School zone safety diagnosis using automated conflicts analysis technique","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia","funders":"","keywords":"Transport engineering; Pedestrian; Neighbourhood (mathematics); Occupational safety and health; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004489164,0.0007974895,0.0005068074,0.004963759,0.0006118058,0.0009059168,0.0008863013,0.0007117494,0.002276897],"category_scores_gemma":[0.001525356,0.000296888,0.00058809,0.001445412,0.0002610039,0.0006466444,0.0007271033,0.0004875791,0.0007599743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005755844,"about_ca_system_score_gemma":0.001351434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01133756,"about_ca_topic_score_gemma":0.01057272,"domain_scores_codex":[0.9991284,0.0001142216,0.00005892344,0.000198228,0.0003508004,0.0001494885],"domain_scores_gemma":[0.9988487,0.0002037779,0.0002140831,0.00008966155,0.000577686,0.00006599209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000610258,0.0005540344,0.07769237,0.0002317274,0.0001444603,0.001058527,0.0006773783,0.0598474,0.09180439,0.002070111,0.005926896,0.7593825],"study_design_scores_gemma":[0.00004390416,0.0003242965,0.06988017,0.00003364493,0.00008138002,0.001061658,0.0008503722,0.8761507,0.04498434,0.002358826,0.004156416,0.00007427784],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3726124,0.0003094557,0.6127177,0.0001721415,0.0001002967,0.0003215945,0.0009133241,0.004309546,0.008543593],"genre_scores_gemma":[0.838681,0.0001243236,0.158474,0.00003623941,0.00002077479,0.0000783034,0.0007190817,0.00006177043,0.001804455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01133756,"threshold_uncertainty_score":0.02254313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082259835494472,"score_gpt":0.215601105777038,"score_spread":0.2047785074220932,"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."}}