{"id":"W1514636114","doi":"10.1109/icip.2003.1246990","title":"Evolutionary design of context-free attentional operators","year":2004,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Context (archaeology); Hierarchy; Perception; Visual perception; Domain (mathematical analysis); Psychophysics; Set (abstract data type); Orientation (vector space); Context model; Human visual system model; Computer vision; Pixel; Hue; Human–computer interaction; Image (mathematics); Mathematics; Object (grammar); Psychology","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":[0.0005752144,0.000383146,0.0004086414,0.0004206819,0.0003939061,0.0006399039,0.0008980749,0.0007277071,0.00221837],"category_scores_gemma":[0.00213579,0.0002976447,0.0003722711,0.0002325478,0.0007230148,0.0005634804,0.000837866,0.0006134625,0.0001691165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006925255,"about_ca_system_score_gemma":0.0005886587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001491306,"about_ca_topic_score_gemma":0.001539095,"domain_scores_codex":[0.9998261,0.00005659996,0.000008309215,0.00002960366,0.00004429108,0.0000349746],"domain_scores_gemma":[0.9996095,0.0002046899,0.00003619199,0.00003135592,0.0000726482,0.00004556816],"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":[0.00005976008,0.00005863977,0.0006013222,0.00004717481,0.00003039367,0.0001443142,0.0001465882,0.8504531,0.01076228,0.1085625,0.0006146281,0.02851923],"study_design_scores_gemma":[0.00001580245,0.00002568261,0.0000772838,0.000004177006,0.000006182499,0.00001837807,0.00001399942,0.9869179,0.0004081931,0.01187876,0.0006288224,0.000004759484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1445374,0.0003112015,0.8424824,0.000303922,0.00006173155,0.0001022289,0.00003535613,0.0001898011,0.01197597],"genre_scores_gemma":[0.8277697,0.0001864532,0.1680588,0.00009664657,0.00001562533,0.0002814694,0.00003414914,0.00004665743,0.003510609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00221837,"threshold_uncertainty_score":0.007421196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02789531206524979,"score_gpt":0.260456132031921,"score_spread":0.2325608199666712,"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."}}