{"id":"W2893759514","doi":"10.1177/1541931218621431","title":"Impact of Cognitive Distractions on Drivers’ Anticipation Behavior in Vehicle-bicycle Conflict Situations","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Distracted driving; Distraction; Anticipation (artificial intelligence); Phone; Driving simulator; Crash; Task (project management); Poison control; Applied psychology; Hazard; Human factors and ergonomics; Psychology; Simulation; Transport engineering; Aeronautics; Computer security; Engineering; Computer science; Cognitive psychology; Medical emergency; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002037407,0.0001331546,0.000190137,0.00007135796,0.0003452339,0.0000277653,0.0001127716,0.0001057533,0.0001679705],"category_scores_gemma":[0.0001026077,0.0001078719,0.0002134311,0.0001356023,0.0002646737,0.0002333326,0.00004686544,0.0002070315,0.000005338646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000986774,"about_ca_system_score_gemma":0.00001820124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004728556,"about_ca_topic_score_gemma":0.00003619453,"domain_scores_codex":[0.9991314,0.00001551426,0.000387593,0.0002003692,0.00009890419,0.0001662251],"domain_scores_gemma":[0.9989736,0.0001603256,0.0004563437,0.00006337315,0.0003009812,0.00004535695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001070198,0.0004051753,0.9036711,0.00001585834,0.0001215605,4.15559e-8,0.08262158,0.00001263522,0.01017284,0.002011734,0.0005793793,0.0002811114],"study_design_scores_gemma":[0.0004790836,0.0002498068,0.9735969,0.00009478782,0.00004772888,8.057883e-7,0.02332711,0.0001604146,0.001862165,0.00005816367,0.00002141179,0.0001015965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958279,0.000003518863,0.000005006268,0.00003434798,0.0001635046,0.0002372279,0.000116667,0.00002247002,0.003589405],"genre_scores_gemma":[0.9997126,0.000005003468,0.00002485307,0.00002361654,0.00006795781,0.00001586062,0.00001142388,0.00001279868,0.0001258147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06992587,"threshold_uncertainty_score":0.439889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04197370803097628,"score_gpt":0.3659118579429735,"score_spread":0.3239381499119973,"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."}}