{"id":"W4391109222","doi":"10.1080/15389588.2023.2298682","title":"Conventional or parking-protected bike lanes? A Full-Bayesian before-and-after assessment","year":2024,"lang":"en","type":"article","venue":"Traffic Injury Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Transport engineering; Intersection (aeronautics); Poisson distribution; Collision; Computer science; Statistics; Engineering; Computer security; Mathematics","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":[0.0222993,0.001033629,0.001651642,0.001001704,0.0007591249,0.001362576,0.00185684,0.001613739,0.004445576],"category_scores_gemma":[0.04438541,0.0009281032,0.001857202,0.0006845712,0.001228879,0.002710651,0.001900019,0.001447857,0.0005979335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002180744,"about_ca_system_score_gemma":0.003474625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02698629,"about_ca_topic_score_gemma":0.04271898,"domain_scores_codex":[0.9848823,0.009002015,0.0005558476,0.001989239,0.002713801,0.0008569335],"domain_scores_gemma":[0.9829119,0.009332867,0.003025737,0.001337712,0.002855469,0.0005362584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01055978,0.008149412,0.6326898,0.001358975,0.002784546,0.0002381851,0.002836889,0.07295979,0.003072795,0.009685717,0.002454703,0.2532094],"study_design_scores_gemma":[0.0006914911,0.02696228,0.6406397,0.0005801227,0.002805163,0.0002066153,0.003769176,0.2954186,0.003723052,0.01602183,0.008834497,0.0003474616],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351232,0.0005979222,0.05688583,0.0005230252,0.00004586552,0.001588835,0.001086439,0.0001522312,0.003996618],"genre_scores_gemma":[0.9736062,0.0002179232,0.02245596,0.0001854052,0.00001715121,0.0006627592,0.0008467532,0.00001603416,0.001991629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02698629,"threshold_uncertainty_score":0.1179314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007468402182742946,"score_gpt":0.2588157190068653,"score_spread":0.2513473168241223,"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."}}