{"id":"W2009384932","doi":"10.1167/9.8.446","title":"Gaze behaviour in the natural environment: Eye movements in video versus the real world","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gaze; CLIPS; Perspective (graphical); Session (web analytics); Eye movement; Eye tracking; Set (abstract data type); Natural (archaeology); Pace; Point (geometry); Sitting; Psychology; Computer science; Computer vision; Cognitive psychology; Artificial intelligence; Medicine; Geography","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":[0.0004913821,0.000195504,0.0002265391,0.0002711626,0.0001707487,0.0004692419,0.0001598229,0.0004032998,0.001158864],"category_scores_gemma":[0.003837236,0.0001157234,0.000128078,0.0001354851,0.0003747154,0.0006205669,0.0003413321,0.0002175199,0.0001588958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001961093,"about_ca_system_score_gemma":0.0001051733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165506,"about_ca_topic_score_gemma":0.001903547,"domain_scores_codex":[0.9996463,0.0001409614,0.00001745494,0.0001161522,0.00004839974,0.00003076994],"domain_scores_gemma":[0.9991265,0.0004637387,0.0001884328,0.00005953926,0.000105725,0.0000560889],"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":[0.002613117,0.00040587,0.07819617,0.0009168102,0.0002487591,0.0004110977,0.009731851,0.000782454,0.8512552,0.0009294468,0.0009229695,0.05358628],"study_design_scores_gemma":[0.000180056,0.002389153,0.9481269,0.0001383363,0.0001961784,0.0006304419,0.004321174,0.0038482,0.03583442,0.001409726,0.002851284,0.00007400917],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946126,0.0004734837,0.003382469,0.00005444872,0.00001885563,0.00003497183,0.00007986479,0.00001961141,0.001323759],"genre_scores_gemma":[0.9970888,0.0002497961,0.001951258,0.00007976914,0.00001409221,0.00005591555,0.00008800157,0.00001019642,0.0004621523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00165506,"threshold_uncertainty_score":0.003876805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154916789449271,"score_gpt":0.2876500966055893,"score_spread":0.2761009287110965,"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."}}