{"id":"W1972182149","doi":"10.1038/modpathol.2010.215","title":"Calculator for ovarian carcinoma subtype prediction","year":2010,"lang":"en","type":"article","venue":"Modern Pathology","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Calgary; Centre for Health Evaluation and Outcome Sciences; Vancouver General Hospital; Calgary Laboratory Services; BC Cancer Agency","funders":"BC Cancer Agency; Eli Lilly Canada; Michael Smith Health Research BC; National Cancer Institute; Sanofi","keywords":"Ovarian carcinoma; Serous carcinoma; Ovarian cancer; Oncology; Serous fluid; Medicine; Tissue microarray; Logistic regression; Internal medicine; Cohort; Anatomical pathology; Pathology; Immunohistochemistry; Cancer","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001665768,0.0004798071,0.001033283,0.003678023,0.0006048169,0.001175242,0.0008637423,0.0005130845,0.00794764],"category_scores_gemma":[0.01016648,0.0003306608,0.0003799224,0.00162323,0.0001719225,0.0007557876,0.0006732896,0.0006439602,0.002166242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005019754,"about_ca_system_score_gemma":0.001127381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002284367,"about_ca_topic_score_gemma":0.002044646,"domain_scores_codex":[0.9993181,0.0001684636,0.00008066956,0.0001165471,0.0002797604,0.00003653664],"domain_scores_gemma":[0.9951172,0.003050346,0.0004024114,0.0003339485,0.0009188616,0.0001772439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002842021,0.000385194,0.07858562,0.0002730158,0.0001927794,0.0003498342,0.00008136515,0.01136192,0.005264769,0.00563608,0.03236607,0.8626613],"study_design_scores_gemma":[0.0009238961,0.000779582,0.05677938,0.0001967681,0.0006340517,0.003587637,0.0001547635,0.8395945,0.03488335,0.02052563,0.04178732,0.0001530949],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.3296612,0.00519849,0.5734938,0.001727487,0.0007185505,0.001005352,0.009027434,0.06042033,0.01874742],"genre_scores_gemma":[0.6054837,0.0007252452,0.3793747,0.0003401004,0.0002572926,0.0007462768,0.004236303,0.0007559271,0.008080451],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.00794764,"threshold_uncertainty_score":0.02658755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01803982317258267,"score_gpt":0.2712445993056805,"score_spread":0.2532047761330978,"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."}}