{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009587758,0.00008980446,0.00009167829,0.00003670814,0.00004911124,0.00001073077,0.00006280139,0.00004081887,0.00002814602],"category_scores_gemma":[0.000009375625,0.00009074958,0.00001951202,0.00006247745,0.00001138751,0.0001148456,0.00000778521,0.00007638644,0.000006862281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002973099,"about_ca_system_score_gemma":0.00009122543,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3593208,"about_ca_topic_score_gemma":0.9269804,"domain_scores_codex":[0.9993479,0.000005116149,0.0002021155,0.0001128764,0.00008522934,0.0002467458],"domain_scores_gemma":[0.9997785,0.00003361425,0.00002599832,0.00008181744,0.00002466512,0.00005539264],"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":[0.0001359209,0.0001662096,0.08197746,0.0005203716,0.000190678,0.00004723817,0.003497224,0.2776563,0.1423777,0.0009122501,0.04040771,0.452111],"study_design_scores_gemma":[0.0008155921,0.00002962042,0.9633197,0.00002131847,0.000006226062,0.000001782008,0.00008283443,0.01156676,0.01735061,0.00002971354,0.006615635,0.0001602607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921231,0.00002101308,0.006801442,0.00002804751,0.0005874947,0.0001818172,0.00003152664,0.0000648164,0.0001607547],"genre_scores_gemma":[0.9918655,0.000003395578,0.007950624,0.00003095863,0.0001013745,0.000009823388,0.00001400113,0.00001725699,0.000007081243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8813422,"threshold_uncertainty_score":0.6449456,"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."}}