{"id":"W4402423703","doi":"10.1016/j.ijhcs.2024.103366","title":"A gaze-based driver distraction countermeasure: Comparing effects of multimodal alerts on driver's behavior and visual attention","year":2024,"lang":"en","type":"article","venue":"International Journal of Human-Computer Studies","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Distraction; Gaze; Countermeasure; Computer science; Human–computer interaction; Eye tracking; Psychology; Cognitive psychology; Artificial intelligence; Engineering","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":[0.0005210685,0.0006586108,0.0004134075,0.0005928526,0.0001627376,0.0003000057,0.0003209127,0.000501712,0.00116259],"category_scores_gemma":[0.003379628,0.0001590955,0.0002677111,0.0001883647,0.0001396402,0.0003379849,0.0003489411,0.0003805373,0.000185433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002032594,"about_ca_system_score_gemma":0.0003050757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006209082,"about_ca_topic_score_gemma":0.0006721145,"domain_scores_codex":[0.999493,0.0001197464,0.00005459133,0.0001156803,0.0001766071,0.00004041583],"domain_scores_gemma":[0.9981407,0.000994278,0.0003183276,0.0001112218,0.0003191763,0.0001163666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02423632,0.004867617,0.04165969,0.00235836,0.0004840441,0.000144043,0.0009735864,0.002023802,0.695571,0.000251746,0.0009469778,0.2264828],"study_design_scores_gemma":[0.001640784,0.09712407,0.5242969,0.0002120494,0.002047701,0.0008886163,0.0007713767,0.01906827,0.3495398,0.0004113574,0.00380435,0.0001946533],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934232,0.000572147,0.004765912,0.00003435706,0.00009201989,0.000183936,0.0001529245,0.0001110646,0.0006644472],"genre_scores_gemma":[0.9911981,0.0003428255,0.007073835,0.0001018025,0.00006836647,0.0003303,0.0001770348,0.00002091127,0.0006867881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00116259,"threshold_uncertainty_score":0.003889263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03517388996523396,"score_gpt":0.4108000878488661,"score_spread":0.3756261978836321,"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."}}