{"id":"W1979100774","doi":"10.1109/icip.2012.6467049","title":"Saliency detection via statistical non-redundancy","year":2012,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Redundancy (engineering); Artificial intelligence; Computer science; Gaussian; Pattern recognition (psychology); Neighbourhood (mathematics); Statistical model; Gaussian process; Statistical analysis; Precision and recall; Computer vision; Algorithm; Data mining; Mathematics; Statistics","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":[0.0006919469,0.000642432,0.0009769636,0.002527038,0.0003527763,0.0005776709,0.001104359,0.0005012039,0.000883441],"category_scores_gemma":[0.002725114,0.0003168629,0.0006206334,0.0008989855,0.0005389197,0.0009550164,0.0009942055,0.0004601995,0.0003494891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004407319,"about_ca_system_score_gemma":0.0005007323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001469442,"about_ca_topic_score_gemma":0.001818553,"domain_scores_codex":[0.9995524,0.00007468089,0.00002438823,0.0001352625,0.0001644418,0.00004877741],"domain_scores_gemma":[0.9990171,0.0003625361,0.0001595423,0.0001392258,0.0002608126,0.00006075325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000412184,0.0001080216,0.002293631,0.0002617495,0.0001428251,0.0003891689,0.000292961,0.03546747,0.1482242,0.01165823,0.003316769,0.7974327],"study_design_scores_gemma":[0.00003384849,0.0002245498,0.004958115,0.00001379154,0.00004756238,0.0006466667,0.00004189839,0.9385929,0.04239146,0.01044289,0.002556223,0.00005011712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03961007,0.0004050694,0.9580792,0.00006825698,0.00004733915,0.00006986351,0.00005498187,0.0009385554,0.0007266385],"genre_scores_gemma":[0.5337784,0.0002638236,0.4640493,0.00006672872,0.000113031,0.0001107027,0.0002165772,0.0001328739,0.001268499],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002527038,"threshold_uncertainty_score":0.003659427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284168742195125,"score_gpt":0.2766479321892262,"score_spread":0.263806244767275,"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."}}