{"id":"W2771407654","doi":"10.3141/2662-01","title":"Comparing Crowdsourced Near-Miss and Collision Cycling Data and Official Bike Safety Reporting","year":2017,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Collision; Odds; Near miss; Computer science; Logistic regression; Data collection; Data science; Computer security; Engineering; Forensic engineering; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.01959835,0.0002282347,0.0006231221,0.0003569827,0.007503815,0.001194677,0.002245942,0.0002389924,0.00009551361],"category_scores_gemma":[0.00241728,0.0001834909,0.0001801467,0.0006676118,0.002990107,0.001939914,0.00004976839,0.00202363,0.000002593169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001455317,"about_ca_system_score_gemma":0.001050933,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06114379,"about_ca_topic_score_gemma":0.3069785,"domain_scores_codex":[0.9916103,0.001098898,0.002301759,0.0006731038,0.003399057,0.0009168694],"domain_scores_gemma":[0.9930531,0.001060429,0.002044125,0.001098074,0.00216263,0.0005815783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009695984,0.00009370526,0.9818221,0.0001425978,0.00006515752,0.00009506018,0.007459464,0.0001269529,0.0004421355,0.0005881562,0.0003940616,0.007800982],"study_design_scores_gemma":[0.001159041,0.0001124049,0.9780067,0.0004243422,0.00006146181,3.031914e-7,0.004467406,0.0007175936,0.0001612216,0.00135558,0.01334605,0.0001878872],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922822,0.000315158,0.0006672652,0.004685225,0.0004554283,0.0008382673,0.00006630255,0.00002852927,0.0006616467],"genre_scores_gemma":[0.996367,0.001222407,0.001533038,0.00001969759,0.0003603037,0.000009153753,0.00002554951,0.00003511393,0.0004276911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2458347,"threshold_uncertainty_score":0.9998422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2761926287462262,"score_gpt":0.4796810141381024,"score_spread":0.2034883853918762,"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."}}