{"id":"W1966470150","doi":"10.1167/14.10.371","title":"Inhibition of attention to irrelevant areas of a scene: Investigating mechanisms of attention during visual search","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Visual search; Fixation (population genetics); Gaze; Saccade; Context (archaeology); Eye movement; Computer science; Cognitive psychology; Latency (audio); Control (management); Psychology; Object (grammar); Artificial intelligence; Computer vision; 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":[0.000508064,0.0004459686,0.0005817309,0.0004578033,0.0002062075,0.0005778541,0.0004286258,0.0003887643,0.0007574109],"category_scores_gemma":[0.003765621,0.000299223,0.0002286895,0.0002590772,0.0003891521,0.0008761858,0.0004687077,0.0005246358,0.0001095775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004817135,"about_ca_system_score_gemma":0.000328366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002500286,"about_ca_topic_score_gemma":0.002103357,"domain_scores_codex":[0.999561,0.00005283586,0.00002848302,0.00011983,0.000179084,0.00005879153],"domain_scores_gemma":[0.9985836,0.0006411081,0.0003826399,0.000153529,0.0001313466,0.0001078941],"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":[0.001399367,0.0002333433,0.01606746,0.0002731811,0.0000449629,0.0001191999,0.001330071,0.0003211575,0.9606175,0.000539268,0.00009238581,0.01896203],"study_design_scores_gemma":[0.0003153651,0.002969665,0.81027,0.00007107596,0.0002351466,0.0007403094,0.0006419253,0.0129892,0.1674049,0.002458002,0.001842858,0.00006152731],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969971,0.0003293344,0.001801562,0.00002122413,0.000004230826,0.00002161568,0.00002510448,0.0000126995,0.0007871217],"genre_scores_gemma":[0.9965329,0.0002211579,0.002498498,0.00003319193,0.000008468483,0.00006197374,0.00008909728,0.00002105032,0.0005335765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002500286,"threshold_uncertainty_score":0.004971504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950976281948921,"score_gpt":0.310248015417785,"score_spread":0.2907382525982958,"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."}}