{"id":"W4413348604","doi":"10.31234/osf.io/tekh3_v1","title":"Eye movements reveal that drivers can predict the location of hazards in dynamic road scenes but gaze and awareness are dissociable","year":2025,"lang":"en","type":"article","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amorfix (Canada)","funders":"Transport Canada","keywords":"Hazard; Eye movement; Computer science; Computer vision; Transport engineering; 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":[0.000130569,0.0002157025,0.0001577305,0.0002746575,0.0001660516,0.0003320096,0.0001203239,0.0003267347,0.003041378],"category_scores_gemma":[0.001369091,0.0001519109,0.0001699941,0.000147843,0.0001431811,0.0004143388,0.0004038891,0.0003964095,0.0005773016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580172,"about_ca_system_score_gemma":0.0002217196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00553888,"about_ca_topic_score_gemma":0.01033729,"domain_scores_codex":[0.9998801,0.000009477887,0.000006568084,0.00004641863,0.00003234241,0.00002512762],"domain_scores_gemma":[0.9997285,0.00008833533,0.00005162367,0.00004293873,0.00005876231,0.00002983572],"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":[0.001099328,0.0003001638,0.1531529,0.0002190844,0.000135066,0.0004050264,0.002059649,0.0009278023,0.7388196,0.0005243636,0.003313994,0.09904297],"study_design_scores_gemma":[0.00001802598,0.0002553686,0.978309,0.00002104739,0.00003551549,0.0002246584,0.0003814195,0.002438067,0.01553293,0.0004264438,0.002334788,0.00002263292],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921841,0.0002172571,0.003622208,0.0001063069,0.00002092842,0.00002771254,0.0006951299,0.0001321028,0.002994191],"genre_scores_gemma":[0.9964336,0.0001309065,0.00149526,0.00008799895,0.000006664886,0.00002035004,0.0004642374,0.00003031673,0.001330795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00553888,"threshold_uncertainty_score":0.01101327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453163574937306,"score_gpt":0.3425746629845174,"score_spread":0.3280430272351443,"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."}}