{"id":"W4231724352","doi":"10.32920/ryerson.14643855.v1","title":"Exploration Of Theoretical And Application Issues In Using Fully Bayesian Methods For Road Safety Analysis","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Univariate; Multivariate statistics; Bayesian probability; Statistics; Poisson regression; Ranking (information retrieval); Poisson distribution; Multivariate analysis; Univariate analysis; Mathematics; Computer science; Econometrics; Medicine; Artificial intelligence","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":[0.07930581,0.001331552,0.001597016,0.002402235,0.001197012,0.003324314,0.00363641,0.002431134,0.003452946],"category_scores_gemma":[0.1987257,0.001269048,0.001346385,0.001951343,0.004335043,0.005642534,0.003245905,0.003121723,0.0004953556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002275131,"about_ca_system_score_gemma":0.003891296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009698487,"about_ca_topic_score_gemma":0.008564135,"domain_scores_codex":[0.9602341,0.03350849,0.0006618162,0.001384977,0.003855386,0.000355118],"domain_scores_gemma":[0.7553992,0.224603,0.003414288,0.007070786,0.008815262,0.0006975684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001284281,0.0001091426,0.007658502,0.0005563062,0.0002659579,0.0002183517,0.0008612928,0.2367291,0.0008368262,0.6094533,0.002007416,0.1411754],"study_design_scores_gemma":[0.00003247178,0.00009673171,0.001225336,0.0002703011,0.00003699199,0.0001168902,0.0001560274,0.6255801,0.000514353,0.3687455,0.00317313,0.00005216667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006664239,0.0006809669,0.9886011,0.001325795,0.00002998551,0.00006776261,0.00005055582,0.00008822147,0.002491318],"genre_scores_gemma":[0.2516777,0.001486347,0.7434283,0.0009546512,0.000183599,0.0004581646,0.0001605693,0.0001506491,0.001500001],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07930581,"threshold_uncertainty_score":0.4194142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08759181864643606,"score_gpt":0.477533983704133,"score_spread":0.3899421650576969,"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."}}