{"id":"W2124719698","doi":"10.2174/1876527001305010006","title":"A Stochastic Model for Highway Accident Predictions with Winter Data","year":2013,"lang":"en","type":"article","venue":"The Open Statistics & Probability Journal","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Poisson distribution; Accident (philosophy); Computer science; Stochastic modelling; Poisson regression; Markov process; Markovian arrival process; Queueing theory; Time horizon; Compound Poisson process; Process (computing); Stochastic process; Poisson process; Operations research; Econometrics; Statistics; Mathematics; Mathematical optimization","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":[0.002567856,0.001008529,0.001129139,0.0009311076,0.0005106749,0.001284935,0.002698014,0.001364042,0.002118448],"category_scores_gemma":[0.006057864,0.0007546437,0.001089749,0.001288514,0.0007054359,0.00165739,0.0008324665,0.001651891,0.0004567272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601002,"about_ca_system_score_gemma":0.001415013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04223596,"about_ca_topic_score_gemma":0.02737196,"domain_scores_codex":[0.9989449,0.0003193353,0.00008051763,0.0003293575,0.0001777013,0.0001481901],"domain_scores_gemma":[0.9973623,0.001447044,0.0004923188,0.0001606479,0.0004361896,0.0001014395],"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":[0.00002846898,0.00001894097,0.001820054,0.00001736354,0.00002388156,0.00005410497,0.00002567449,0.985754,0.0001981888,0.008846046,0.0004411626,0.0027721],"study_design_scores_gemma":[0.000003715855,0.000006288624,0.0002077539,0.000002086275,0.000004220143,0.000006448809,0.000004262818,0.9973213,0.0000414301,0.002244365,0.0001538776,0.000004250071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1237488,0.0004282444,0.868227,0.0009638063,0.0001251604,0.0001005217,0.00316936,0.0008235205,0.002413563],"genre_scores_gemma":[0.9531364,0.0005193905,0.03726168,0.0001355405,0.0001648031,0.0002749152,0.003210137,0.00008832471,0.005208769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04223596,"threshold_uncertainty_score":0.08398026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05592445360724953,"score_gpt":0.2787064547856495,"score_spread":0.2227820011783999,"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."}}