{"id":"W4387845939","doi":"10.1177/21695067231192557","title":"Drivers’ trust & reliance on automated braking at intersections: Effects of automation braking profile & in-vehicle displays","year":2023,"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":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Automation; Brake; Threshold braking; Dynamic braking; Electronic brakeforce distribution; Engine braking; Computer science; Automotive engineering; Simulation; Braking system; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002310073,0.0004777762,0.0003813183,0.0002553707,0.0003831703,0.001266042,0.0003084792,0.0004768555,0.002671077],"category_scores_gemma":[0.01962793,0.0004331793,0.0003313507,0.0001637836,0.0005061593,0.0007856655,0.0005704541,0.0006904494,0.0002686839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004433442,"about_ca_system_score_gemma":0.0003405811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003742522,"about_ca_topic_score_gemma":0.004680529,"domain_scores_codex":[0.9983672,0.0006219571,0.0001848507,0.0002465055,0.0003964889,0.0001829806],"domain_scores_gemma":[0.9707851,0.01907465,0.005362002,0.001450835,0.002010864,0.001316579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.04363573,0.02493178,0.6496083,0.001103185,0.001170697,0.0005788834,0.04911336,0.004070781,0.157401,0.0004868487,0.0009465178,0.06695302],"study_design_scores_gemma":[0.0004815981,0.02032793,0.9538823,0.00003830022,0.0003253914,0.0001184392,0.007308035,0.003135431,0.01307526,0.0002326552,0.0009669979,0.0001076021],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996539,0.000008570595,0.0000898832,0.000005021761,0.000002070233,0.00001353863,0.00001808953,0.000002830617,0.0002061072],"genre_scores_gemma":[0.9992643,0.00001679548,0.000300106,0.00001057946,0.000002746804,0.00003610153,0.00003549258,0.000002747988,0.0003311989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003742522,"threshold_uncertainty_score":0.01221693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02213706843324226,"score_gpt":0.3069514720027099,"score_spread":0.2848144035694677,"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."}}