{"id":"W4394683868","doi":"10.1186/s41235-024-00549-7","title":"On investigating drivers’ attention allocation during partially-automated driving","year":2024,"lang":"en","type":"article","venue":"Cognitive Research Principles and Implications","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Inattentional blindness; Task (project management); Computer science; Surprise; Automation; Human–computer interaction; Control (management); Eye tracking; Simulation; Psychology; Artificial intelligence; Engineering; Perception; Communication","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007067095,0.000132863,0.000113394,0.0004656761,0.0008525926,0.0002959292,0.0001169054,0.00009453437,0.0008418093],"category_scores_gemma":[0.0006913815,0.0001315835,0.00005692396,0.0005451532,0.0002292177,0.000278734,0.0001046796,0.0004703423,0.001296148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294582,"about_ca_system_score_gemma":0.00008235109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003026476,"about_ca_topic_score_gemma":0.00004257867,"domain_scores_codex":[0.9980994,0.0003909713,0.000339876,0.0005205148,0.0002775926,0.0003716707],"domain_scores_gemma":[0.9980741,0.001009317,0.00006232899,0.0002308698,0.0004396847,0.0001837524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004761184,0.0003514806,0.01967936,0.0002231367,0.0003754788,0.00002095213,0.009643825,0.00005602465,0.0556822,0.8649957,0.004862453,0.04406177],"study_design_scores_gemma":[0.0003837977,0.00009865552,0.9783136,0.0005604257,0.00002117394,0.00003493888,0.002491711,0.01087134,0.0006928517,0.002114312,0.004234338,0.000182845],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9612313,0.0001280317,0.002103225,0.003042838,0.0002037955,0.0006111064,0.00003528276,0.0007975566,0.03184687],"genre_scores_gemma":[0.9956972,0.00006215287,0.00006900894,0.00008233698,0.0001286776,0.0005143721,0.0001150019,0.00002807207,0.003303151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9586343,"threshold_uncertainty_score":0.9994814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1663847983105939,"score_gpt":0.4851708520745794,"score_spread":0.3187860537639855,"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."}}