{"id":"W3190031958","doi":"10.1177/00187208211026133","title":"Anticipatory Driving in Automated Vehicles: The Effects of Driving Experience and Distraction","year":2021,"lang":"en","type":"article","venue":"Human Factors The Journal of the Human Factors and Ergonomics Society","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Distraction; Anticipation (artificial intelligence); Driving simulator; Task (project management); Distracted driving; Poison control; Event (particle physics); Human multitasking; Applied psychology; Psychology; Simulation; Computer science; Cognitive psychology; Engineering; Artificial intelligence","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":[0.0005137956,0.0003007849,0.0001882196,0.000302304,0.0001629233,0.0006804849,0.0002370397,0.000269256,0.001377486],"category_scores_gemma":[0.004252172,0.0001759938,0.000273646,0.0001157097,0.0002277471,0.0003551676,0.0005791174,0.0002664286,0.00009400541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001995489,"about_ca_system_score_gemma":0.0002961264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001585437,"about_ca_topic_score_gemma":0.002269893,"domain_scores_codex":[0.9995566,0.0001088437,0.00003500978,0.00009530123,0.0001255159,0.00007873085],"domain_scores_gemma":[0.9952466,0.002617283,0.001332585,0.0001301353,0.0002768349,0.0003966638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005068464,0.002118378,0.8529189,0.0006035818,0.0002808541,0.0007083157,0.006773583,0.001417939,0.07951578,0.0001399873,0.0001849534,0.05026934],"study_design_scores_gemma":[0.00001860092,0.002484596,0.9905695,0.00003241903,0.00006537561,0.000230035,0.001306797,0.001004894,0.003887387,0.00006865897,0.0003129255,0.00001878676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995021,0.00007154026,0.0002049118,0.000006586459,0.000001874638,0.000007161817,0.00001877167,0.000002613639,0.000184404],"genre_scores_gemma":[0.9995314,0.0000518728,0.0002544144,0.000006863178,0.000002830821,0.00001097749,0.0000361589,0.000001416155,0.0001040508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001585437,"threshold_uncertainty_score":0.004608154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0270193757166059,"score_gpt":0.3295998713488292,"score_spread":0.3025804956322233,"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."}}