{"id":"W2151131460","doi":"10.5858/133.1.31","title":"Measuring extent of ductal carcinoma in situ in breast excision specimens: a comparison of 4 methods.","year":2009,"lang":"en","type":"article","venue":"PubMed","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ductal carcinoma; Sampling (signal processing); Context (archaeology); Carcinoma; Medicine; Carcinoma in situ; Radiology; Calcification; Breast carcinoma; In situ; Statistics; Breast cancer; Computer science; Mathematics; Pathology; Internal medicine; Biology; Computer vision; Cancer","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":[0.0118808,0.0007313651,0.0005827061,0.00376521,0.0002895752,0.0006303104,0.0007711113,0.0005935404,0.0005766502],"category_scores_gemma":[0.01804963,0.0005201756,0.0006042574,0.001456368,0.0007304048,0.0008996869,0.001008847,0.0002982157,0.0002843528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003702062,"about_ca_system_score_gemma":0.0003244083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006946105,"about_ca_topic_score_gemma":0.002299098,"domain_scores_codex":[0.9938604,0.002539403,0.0008534741,0.0006909242,0.001944481,0.0001113071],"domain_scores_gemma":[0.9781948,0.01118455,0.004647353,0.002316846,0.003171674,0.0004847806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002447648,0.0001163354,0.8378368,0.001347644,0.0006862248,0.0003546052,0.0007443194,0.0008369514,0.04934581,0.0001668756,0.0001536672,0.1059631],"study_design_scores_gemma":[0.00005346576,0.002682572,0.9516283,0.0003312122,0.0006511079,0.006633767,0.0007062639,0.003846436,0.03031102,0.0002566039,0.002833802,0.00006540413],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9466305,0.02920824,0.02103557,0.00009267887,0.00012278,0.0003014824,0.0003806883,0.0001442418,0.002083811],"genre_scores_gemma":[0.9199067,0.007188206,0.07164892,0.00005508262,0.00006194369,0.0001867739,0.0005051189,0.00005756627,0.0003896294],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0118808,"threshold_uncertainty_score":0.06283242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05067072494012278,"score_gpt":0.3053493487689166,"score_spread":0.2546786238287938,"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."}}