{"id":"W4375855151","doi":"10.1016/j.aap.2023.107097","title":"Analysis of driver characteristics, self-reported psychology measures and driving performance measures associated with aggressive driving","year":2023,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; University of Windsor","keywords":"Aggressive driving; Poison control; Driving simulator; Human factors and ergonomics; Injury prevention; Structural equation modeling; Brake; Applied psychology; Occupational safety and health; Suicide prevention; Driving under the influence; Dangerous driving; Engineering; Safe driving; Psychology; Simulation; Computer science; Automotive engineering; Medical emergency; Medicine; Machine learning","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":[0.000742102,0.0002384892,0.0007294953,0.001380293,0.0001370169,0.00004078534,0.0001622275,0.0001444718,0.00006267073],"category_scores_gemma":[0.0001205365,0.0002163112,0.0003448521,0.003974108,0.00004686883,0.0002519879,0.00004814102,0.0001682842,0.000006056986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007292884,"about_ca_system_score_gemma":0.00001808758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001557252,"about_ca_topic_score_gemma":0.00284271,"domain_scores_codex":[0.9980636,0.0001287081,0.0006603195,0.0003727076,0.0004642793,0.0003104384],"domain_scores_gemma":[0.9986986,0.00008704957,0.0005618755,0.0003518452,0.0002190829,0.0000815651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008971486,0.00004489221,0.922785,0.000004744425,0.03057421,0.00001242316,0.0004517149,0.03398652,0.0004543888,0.000002993978,0.000036527,0.01163758],"study_design_scores_gemma":[0.0002709047,0.0000317692,0.8688904,0.0000814972,0.01951496,0.000001637822,0.0000562057,0.110814,0.0001058854,0.000006133875,0.00001968924,0.0002068868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887342,0.0001519572,0.0103449,0.00001858875,0.00008638968,0.0001355434,0.000001076058,0.0004344079,0.00009296044],"genre_scores_gemma":[0.997933,0.001467878,0.0001075573,0.000005126431,0.00002702897,0.00001958097,0.0003082026,0.00002747072,0.0001042008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0768275,"threshold_uncertainty_score":0.8820915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348370030154591,"score_gpt":0.2534790195791647,"score_spread":0.2399953192776188,"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."}}