{"id":"W4310608228","doi":"","title":"Unsupervised Malignant Mammographic Breast Mass Segmentation Algorithm Based On Pickard Markov Random Field","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Markov random field; Artificial intelligence; Segmentation; Random field; Markov process; Pattern recognition (psychology); Algorithm; Image segmentation; 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":[0.0005498918,0.000513778,0.001205312,0.00185048,0.0006513104,0.0006981561,0.001211065,0.0009780602,0.001535713],"category_scores_gemma":[0.0008447004,0.0004857319,0.001017708,0.0006991729,0.0003827116,0.0005901718,0.0006161072,0.0006087054,0.0006400195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005338175,"about_ca_system_score_gemma":0.00153247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009138396,"about_ca_topic_score_gemma":0.0132356,"domain_scores_codex":[0.9996539,0.00003909224,0.00002006926,0.0001123697,0.0001252216,0.00004934991],"domain_scores_gemma":[0.999557,0.0001785065,0.00004181007,0.00004178838,0.0001478474,0.00003298871],"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":[0.0005513681,0.0002544261,0.008620198,0.0002160361,0.0001803833,0.0004481665,0.0001783605,0.1411833,0.06869261,0.006806111,0.004820937,0.768048],"study_design_scores_gemma":[0.00001459776,0.00004540534,0.002256459,0.000009504671,0.00004614448,0.0002518975,0.00001498264,0.9847755,0.009797613,0.001672875,0.001097179,0.00001788538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04696023,0.0005719484,0.949474,0.0001582356,0.0000513441,0.00009263938,0.0001360012,0.001601768,0.0009537889],"genre_scores_gemma":[0.3618661,0.0006492553,0.630919,0.0002022501,0.0001191781,0.0001375317,0.0007929462,0.0002249002,0.005088837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009138396,"threshold_uncertainty_score":0.01817042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006610380100650399,"score_gpt":0.2016156965948969,"score_spread":0.1950053164942465,"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."}}