{"id":"W2074678338","doi":"10.5244/c.24.110","title":"Saliency Segmentation based on Learning and Graph Cut Refinement","year":2010,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Artificial intelligence; Segmentation; Image segmentation; Graph; Computer vision; Pattern recognition (psychology); Theoretical 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":[0.0001944727,0.0000646728,0.00004529121,0.0001138492,0.0001532298,0.00009548276,0.00009433847,0.00002879229,0.0001202678],"category_scores_gemma":[0.00001848909,0.00005389606,0.00002334959,0.000188466,0.00001632541,0.0001636155,0.00002853355,0.0001314239,0.0000388902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006889167,"about_ca_system_score_gemma":0.000009159759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001683778,"about_ca_topic_score_gemma":0.00003662577,"domain_scores_codex":[0.9993599,0.00003373124,0.0001046329,0.0002161213,0.0001836306,0.0001019655],"domain_scores_gemma":[0.9997417,0.00002126017,0.00003790061,0.0001190064,0.00002909,0.00005100861],"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":[0.00002495185,0.0003942194,0.02423586,0.00003053035,0.00001158418,0.000006398963,0.0006041766,0.0005399266,0.3091899,0.166654,0.000857164,0.4974513],"study_design_scores_gemma":[0.001901189,0.001654167,0.0559779,0.0000253051,0.00001101383,0.00001678015,0.0002433308,0.8259403,0.09384218,0.003706536,0.01609361,0.0005877591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3248295,0.000002447416,0.6572138,0.001015195,0.0005695513,0.0001115055,1.565555e-7,0.0002625809,0.01599521],"genre_scores_gemma":[0.9858921,0.000003003177,0.01277445,0.0004666234,0.00001838323,0.0000098166,0.000001825329,0.000003080419,0.0008306867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8254003,"threshold_uncertainty_score":0.2197818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009763177913905144,"score_gpt":0.274348624450405,"score_spread":0.2645854465364999,"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."}}