{"id":"W4400645479","doi":"10.1109/iv55156.2024.10588589","title":"Understanding and Modeling the Effects of Task and Context on Drivers’ Gaze Allocation","year":2024,"lang":"en","type":"article","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Gaze; Computer science; Task (project management); Context (archaeology); Human–computer interaction; Context model; Artificial intelligence; Engineering; Systems engineering; Geography","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":[0.0003804882,0.0007120737,0.0003266104,0.0005563073,0.0001862551,0.0006226295,0.0006327957,0.0005934533,0.001100172],"category_scores_gemma":[0.001866048,0.0003601551,0.0005971367,0.0002452441,0.0002003234,0.0008177457,0.0005158119,0.0007037263,0.0003512998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007099637,"about_ca_system_score_gemma":0.0008102827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04707239,"about_ca_topic_score_gemma":0.05441432,"domain_scores_codex":[0.9998159,0.00002776414,0.000006964754,0.00007970732,0.00002361964,0.00004612314],"domain_scores_gemma":[0.9996148,0.0001855309,0.00004140896,0.00003849508,0.00009606995,0.00002376404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004971302,0.0002639919,0.05317535,0.0002497699,0.0001789862,0.000323895,0.000755507,0.7775654,0.04894281,0.003672969,0.003816268,0.110558],"study_design_scores_gemma":[0.000005740822,0.00003630121,0.01059781,0.000009081259,0.0000171889,0.00003162684,0.00003652321,0.9861786,0.001384832,0.001153398,0.0005380209,0.00001077458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7766209,0.001813659,0.2139499,0.0006741866,0.0001412594,0.00009724725,0.001592719,0.001138629,0.003971519],"genre_scores_gemma":[0.9847144,0.0003790379,0.01219112,0.0000508461,0.00003808691,0.00004810285,0.000536642,0.00004683492,0.001994895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04707239,"threshold_uncertainty_score":0.09359676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08934128534702793,"score_gpt":0.3552283012661992,"score_spread":0.2658870159191713,"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."}}