{"id":"W2013525041","doi":"10.1016/j.imavis.2008.02.006","title":"Semiautomatic segmentation with compact shape prior","year":2008,"lang":"en","type":"article","venue":"Image and Vision Computing","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"Insight Design Labs (Canada); Western University","funders":"","keywords":"Segmentation; Computer vision; Artificial intelligence; Computer science; Pattern recognition (psychology); Mathematics","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":[0.0002565203,0.0001349255,0.0001644206,0.0001032236,0.0003233973,0.0001748395,0.000258591,0.00003109518,0.0000297258],"category_scores_gemma":[0.0000366758,0.0001050356,0.00002451849,0.0002666293,0.0001122158,0.0007720352,0.000134261,0.0001235619,0.00002333883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002612695,"about_ca_system_score_gemma":0.0000397279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001206675,"about_ca_topic_score_gemma":2.786566e-7,"domain_scores_codex":[0.9987887,0.00007776207,0.0002553653,0.0003178654,0.0003579869,0.0002022774],"domain_scores_gemma":[0.999253,0.0001694088,0.0001339865,0.0002317853,0.00008537713,0.0001264239],"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":[0.0000119885,0.0001373702,0.00264847,0.0001006092,0.00002279364,0.0002236586,0.004131081,0.00002331168,0.04806909,0.0002037751,0.00592282,0.9385051],"study_design_scores_gemma":[0.001272091,0.0004846971,0.03155041,0.0002975313,0.00001045761,0.0005912015,0.0001537145,0.8721055,0.09286102,0.000194797,0.00009151458,0.0003870937],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1869652,0.00003925934,0.8115757,0.0003435384,0.00003940686,0.0001798434,3.600025e-7,0.000410641,0.0004460354],"genre_scores_gemma":[0.5261539,0.00001538812,0.4732009,0.0005547898,0.00002946634,0.000001387869,0.000002898893,0.000007324199,0.00003394371],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9381179,"threshold_uncertainty_score":0.4283226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164291218632534,"score_gpt":0.3241962619706669,"score_spread":0.3077671401074135,"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."}}