{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000582508,0.0002227293,0.0003541125,0.0000525953,0.0008439419,0.0001017086,0.0003468788,0.0001307348,0.0001282118],"category_scores_gemma":[0.0001130285,0.0001208688,0.0002833488,0.000126998,0.0003908845,0.0002584929,0.0001441561,0.0006525116,8.927921e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001352074,"about_ca_system_score_gemma":0.00004199928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001135261,"about_ca_topic_score_gemma":0.000134991,"domain_scores_codex":[0.9981985,0.0004542157,0.0007297007,0.000178783,0.0001995366,0.000239256],"domain_scores_gemma":[0.9978411,0.0007785712,0.0008544,0.0003533104,0.00009532405,0.0000773124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001960629,0.000189004,0.7895692,0.00006505832,0.0002645811,0.000002834178,0.1484556,0.0000758711,0.05899554,0.000883535,0.001369654,0.0001095246],"study_design_scores_gemma":[0.0004792408,0.00005575829,0.9682651,0.0001454213,0.00006940986,0.00002406099,0.02630446,0.0002108819,0.003885285,0.00009907788,0.0003314198,0.0001298375],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998436,0.0001867702,0.00002977033,0.00007245909,0.001011001,0.0001414702,0.000003325618,0.00002697232,0.00009222123],"genre_scores_gemma":[0.9994839,0.0001194096,0.000007177936,0.00008205215,0.0000819471,0.000002649133,0.000002169757,0.0000208737,0.0001998253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1786959,"threshold_uncertainty_score":0.6491004,"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."}}