{"id":"W2565347376","doi":"10.1016/j.aap.2016.11.019","title":"Cyclist deceleration rate as surrogate safety measure in Montreal using smartphone GPS data","year":2016,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Poison control; Measure (data warehouse); Reliability (semiconductor); Crash; Global Positioning System; Ranking (information retrieval); Work (physics); Computer science; Transport engineering; Occupational safety and health; Engineering; Statistics; Simulation; Data mining; Mathematics; Medicine; Machine learning; Medical emergency; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009966625,0.0002006386,0.0003421827,0.0003448892,0.00009555282,0.00005629183,0.0003028709,0.0001183342,0.0003621136],"category_scores_gemma":[0.00006122671,0.0001632573,0.0001807509,0.0008044188,0.00001783493,0.0008659629,0.00009001267,0.0001062916,0.0001112909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002119329,"about_ca_system_score_gemma":0.00002792276,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008414085,"about_ca_topic_score_gemma":0.08741268,"domain_scores_codex":[0.9983007,0.0001658071,0.0005871605,0.000399004,0.0002681433,0.0002791822],"domain_scores_gemma":[0.9990242,0.00006295904,0.0001147151,0.0006660132,0.0000570711,0.00007506478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001730747,0.0001545647,0.6340861,0.000009407547,0.00203682,0.00002780542,0.0002274107,0.2012083,0.01127688,0.0001122531,0.0005612432,0.1501262],"study_design_scores_gemma":[0.001042099,0.00001155511,0.8939833,0.00009037982,0.0009775502,0.000002785153,0.00003918151,0.1023625,0.0006926641,0.000317197,0.0002019993,0.0002788208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8332645,0.0003229399,0.1653152,0.0001033131,0.0001832227,0.0001749236,0.000004131755,0.0001449084,0.0004869248],"genre_scores_gemma":[0.9981832,0.0005346536,0.0004190052,0.000009304475,0.00009158937,0.000006873263,0.0004110932,0.00002362525,0.0003206674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2598972,"threshold_uncertainty_score":0.9292397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02648587102487928,"score_gpt":0.2700804502121247,"score_spread":0.2435945791872454,"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."}}