{"id":"W2894256450","doi":"10.1136/injuryprevention-2018-safety.160","title":"PW 0757 Vision zero in canada: building multi-sectoral capacity for implementation","year":2018,"lang":"en","type":"article","venue":"Abstracts","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parachute","funders":"","keywords":"Zero (linguistics); Computer science; Transport engineering; Engineering; Forensic engineering","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":[0.04943369,0.001271451,0.0008752555,0.004367845,0.01873636,0.01668347,0.006551655,0.004718595,0.03624843],"category_scores_gemma":[0.07470075,0.001260726,0.001570078,0.003197751,0.01054507,0.008462539,0.02885477,0.007733105,0.005605205],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1532379,"about_ca_system_score_gemma":0.708091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9574156,"about_ca_topic_score_gemma":0.9679258,"domain_scores_codex":[0.9535077,0.01178321,0.001102917,0.002844417,0.01480214,0.0159596],"domain_scores_gemma":[0.878862,0.008606977,0.002056379,0.004825075,0.04997648,0.05567303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001950489,0.0005877255,0.01996658,0.001248079,0.0001169515,0.0007233724,0.01638718,0.003856069,0.001769447,0.1336006,0.5603405,0.2612084],"study_design_scores_gemma":[0.0001518051,0.0003285304,0.02617743,0.002285356,0.00007591208,0.0001532778,0.03398904,0.005468129,0.001083697,0.03973495,0.8902999,0.0002520752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04861547,0.003559752,0.04220916,0.3895665,0.003434365,0.005441567,0.004105659,0.002721312,0.5003462],"genre_scores_gemma":[0.6552803,0.004823814,0.1379719,0.0500493,0.0005265807,0.004766615,0.006697468,0.001266048,0.1386179],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1532379,"threshold_uncertainty_score":0.982124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02417565581282537,"score_gpt":0.2778737905441144,"score_spread":0.253698134731289,"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."}}