{"id":"W4401513785","doi":"10.1177/03611981241265849","title":"Evaluation of Conventional Surrogate Indicators of Safety for Connected and Automated Vehicles in Car Following at Signalized Intersections","year":2024,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"Centre interuniversitaire de recherche sur les reseaux d'entreprise, la logistique et le transport","keywords":"Crash; Collision; Acceleration; Automotive engineering; Computer science; Poison control; Simulation; Engineering; Transport engineering; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005403224,0.001088099,0.0006402489,0.002291204,0.0003425762,0.001301066,0.0009597039,0.000843649,0.0005220115],"category_scores_gemma":[0.02612362,0.0003044066,0.0007836964,0.001207541,0.0006583984,0.001470678,0.00107308,0.0006712097,0.0001081798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001107089,"about_ca_system_score_gemma":0.001292055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004906469,"about_ca_topic_score_gemma":0.003416466,"domain_scores_codex":[0.9960725,0.001500453,0.0002863734,0.0004356723,0.001444253,0.0002606552],"domain_scores_gemma":[0.9810985,0.009911516,0.003717673,0.001198024,0.003423969,0.0006502836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001813451,0.0007809242,0.2411605,0.0004444542,0.0004250189,0.0001893492,0.0003201491,0.6934004,0.006347916,0.00266137,0.000430969,0.05202548],"study_design_scores_gemma":[0.00005275873,0.002227135,0.06125169,0.00007934129,0.0001477062,0.00009743439,0.0003482059,0.9265259,0.00778603,0.0009852018,0.0004406683,0.00005799222],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750085,0.0002243598,0.02335243,0.00005131704,0.0000278614,0.00008817897,0.0002147795,0.000145367,0.0008872233],"genre_scores_gemma":[0.9948654,0.00004930024,0.004788101,0.00000525633,0.000003614332,0.00002994406,0.0001852876,0.000006632235,0.00006664117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005403224,"threshold_uncertainty_score":0.0285753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05261402788323891,"score_gpt":0.3636949766145749,"score_spread":0.311080948731336,"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."}}