{"id":"W2914152816","doi":"10.1177/0361198118821672","title":"Safe Streets for All? Analyzing Infrastructural Response to Pedestrian and Cyclist Crashes in New York City, 2009–2018","year":2019,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Pedestrian; Crash; Investment (military); Case fatality rate; Injury prevention; Business; Occupational safety and health; Demographic economics; Poison control; Distribution (mathematics); Transport engineering; Geography; Environmental health; Engineering; Medicine; Economics; Political science; Computer science","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":[0.0005320576,0.0003541294,0.0002762819,0.001855065,0.0006867193,0.001081422,0.0008034889,0.0005570265,0.003184712],"category_scores_gemma":[0.002556341,0.0002655939,0.0005290769,0.002101293,0.0003818857,0.001093109,0.001699395,0.0008575881,0.0006112608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002184229,"about_ca_system_score_gemma":0.00201172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4489123,"about_ca_topic_score_gemma":0.5826789,"domain_scores_codex":[0.9996179,0.00004394036,0.00004913292,0.0001059236,0.00007416777,0.0001089532],"domain_scores_gemma":[0.998259,0.0001542619,0.0006234634,0.00007984973,0.0004973219,0.0003860682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001797371,0.00002261288,0.996742,0.00001309079,0.00003332527,0.000024667,0.0002364233,0.0001334908,0.00004212472,0.00003240715,0.00143721,0.001264674],"study_design_scores_gemma":[0.000001377732,0.00001214075,0.9970578,0.00001612058,0.00001065012,0.00001373604,0.001702297,0.000391975,0.00002092307,0.00001331561,0.0007564388,0.000003270913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887456,0.0001940131,0.0001689415,0.0003741921,0.00002978081,0.00003304049,0.00923872,0.00001280344,0.00120281],"genre_scores_gemma":[0.9861124,0.0002583009,0.0002746939,0.00007581355,0.00004149576,0.0001150031,0.01167216,0.00001096465,0.001439058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4489123,"threshold_uncertainty_score":0.8925987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1199001825218822,"score_gpt":0.4256349716853288,"score_spread":0.3057347891634465,"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."}}