{"id":"W4404446994","doi":"10.2139/ssrn.5023242","title":"Prediction and Control of Traffic Accidents on Residential Streets Using the Expert System (Pctars-Es)","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Control (management); Transport engineering; Computer science; Engineering; 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":[0.0005414757,0.000444341,0.0005211455,0.000519648,0.0002012736,0.0004709644,0.0004103737,0.0007255165,0.001704919],"category_scores_gemma":[0.001584053,0.0001907952,0.0002701815,0.0002646627,0.0001593869,0.0003340142,0.0003363608,0.0003842034,0.0003622634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002911623,"about_ca_system_score_gemma":0.0006203883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01498538,"about_ca_topic_score_gemma":0.01082892,"domain_scores_codex":[0.9997601,0.00006599545,0.00001704472,0.0000769594,0.00004835155,0.0000314712],"domain_scores_gemma":[0.999175,0.0004721017,0.00006759659,0.00005650848,0.0001758874,0.00005278494],"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":[0.0005290669,0.0002404401,0.007145519,0.00008654234,0.00005543401,0.0001065665,0.00004676318,0.8619707,0.007092617,0.0005758905,0.001517082,0.1206333],"study_design_scores_gemma":[0.0000162653,0.00006550104,0.001899298,0.000001972874,0.000008870845,0.000009212851,0.000005284822,0.9967642,0.0009361655,0.0002097487,0.0000787345,0.00000474464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5987736,0.0001689953,0.3939012,0.0001242567,0.00006529209,0.0001143969,0.0006007654,0.003228666,0.00302288],"genre_scores_gemma":[0.9685743,0.00004124861,0.02991372,0.00002271444,0.00001667003,0.00005234232,0.0002913412,0.00002046026,0.001067339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01498538,"threshold_uncertainty_score":0.0297963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01024076273552222,"score_gpt":0.23200259756082,"score_spread":0.2217618348252978,"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."}}