{"id":"W1968750665","doi":"10.1016/j.ssci.2005.09.001","title":"Transferability of accident prediction models","year":2005,"lang":"en","type":"article","venue":"Safety Science","topic":"Traffic and Road Safety","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Negative binomial distribution; Accident (philosophy); Term (time); Constant (computer programming); Transferability; Poison control; Mathematical model; Computer science; Statistics; Operations research; Engineering; Econometrics; Simulation; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003920663,0.00006417486,0.00008942195,0.00005117478,0.000078634,0.00000606987,0.0002121881,0.00003014233,0.00003898908],"category_scores_gemma":[0.000007752798,0.00005689646,0.00003627352,0.0003240184,0.0001893018,0.0004981112,0.00001360415,0.00007352991,0.00001068904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009179568,"about_ca_system_score_gemma":0.00004534093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000499219,"about_ca_topic_score_gemma":0.00001677891,"domain_scores_codex":[0.9992034,0.000006133651,0.0002068485,0.0001450007,0.000260555,0.0001779938],"domain_scores_gemma":[0.9996752,0.00001445262,0.00000954565,0.0001932927,0.00004129286,0.00006627961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007575448,0.00001707204,0.001138871,0.000009338318,0.000002470506,8.3716e-8,0.000620272,0.9520196,0.002986664,0.002678304,0.00002702494,0.0404927],"study_design_scores_gemma":[0.0002102929,0.00002235016,0.2521946,0.00001450773,0.000005553369,0.000003027694,0.0000579655,0.7358147,0.00992499,0.0005919509,0.001063258,0.0000968442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7726652,0.0001728364,0.1972952,0.0002450486,0.0004360494,0.0001769206,0.00002551641,0.0003498452,0.0286334],"genre_scores_gemma":[0.9984159,0.00008416241,0.001419862,0.000009804225,0.00004145206,0.000002241823,0.000001011014,0.000004695808,0.00002081509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2510557,"threshold_uncertainty_score":0.232017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008210107266712653,"score_gpt":0.197421381490095,"score_spread":0.1892112742233823,"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."}}