{"id":"W2141561441","doi":"10.1145/2325722.2325726","title":"Visual and emotional salience influence eye movements","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Applied Perception","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Salience (neuroscience); Psychology; Gaze; Cognitive psychology; Stimulus (psychology); Cognition; Eye movement; Eye tracking; Visual perception; Perception; Neuroscience; Computer vision; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002410393,0.000167482,0.0001094176,0.0001861755,0.0004052747,0.0001042076,0.0003018146,0.00009485134,0.0001840208],"category_scores_gemma":[0.000008159041,0.0001680502,0.00005247704,0.0003730136,0.00006942087,0.0009331293,0.0000216817,0.0001958836,0.0004379515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008710846,"about_ca_system_score_gemma":0.00001447486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001532074,"about_ca_topic_score_gemma":0.000003469184,"domain_scores_codex":[0.9986659,0.00004453726,0.000225204,0.0003633525,0.0003891464,0.0003119123],"domain_scores_gemma":[0.9993437,0.00003127959,0.00006129656,0.0003515926,0.00004530372,0.0001668203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007461293,0.001177979,0.003491883,0.00004108538,0.00003866338,6.780404e-7,0.003518387,0.001741204,0.2323875,0.009012718,0.00004712259,0.7484682],"study_design_scores_gemma":[0.001036178,0.0003863393,0.9738872,0.00004262994,0.00002154115,0.00002783601,0.0007906395,0.01224798,0.006810157,0.002645544,0.001457894,0.0006460628],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4885411,0.00000394811,0.5104554,0.0001462001,0.0002146777,0.0001268367,0.000001761008,0.0001458864,0.0003642284],"genre_scores_gemma":[0.989363,0.00004037484,0.009466491,0.0007465311,0.00005850606,0.00006921617,0.000004768461,0.00001018688,0.0002409305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9703953,"threshold_uncertainty_score":0.6852888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657148781443619,"score_gpt":0.2905390978763299,"score_spread":0.2739676100618937,"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."}}