{"id":"W2299201707","doi":"10.1097/pgp.0000000000000274","title":"An Immunohistochemical Algorithm for Ovarian Carcinoma Typing","year":2016,"lang":"en","type":"article","venue":"International Journal of Gynecological Pathology","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":230,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; University of Calgary; Université de Montréal; University of Alberta; University of British Columbia; Alberta Health Services; University of Ottawa; Calgary Laboratory Services; Foothills Medical Centre","funders":"Canadian Institutes of Health Research; Cure Brain Cancer Foundation; University Health Network; Terry Fox Research Institute; Ontario Institute for Cancer Research; BC Cancer Agency; Calgary Laboratory Services","keywords":"Immunohistochemistry; Pathology; Typing; Carcinoma; Ovarian carcinoma; Medicine; Biology; Internal medicine; Ovarian cancer; Cancer; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002844331,0.0001075017,0.0003073249,0.000113064,0.00002966923,0.00001207378,0.0002192799,0.000141291,0.0005132472],"category_scores_gemma":[0.0003695477,0.00006075898,0.00020414,0.00003111085,0.0001010049,0.00009337751,0.00003056938,0.0001129465,0.00001382185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003636188,"about_ca_system_score_gemma":0.0001277012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002887717,"about_ca_topic_score_gemma":9.098042e-7,"domain_scores_codex":[0.998996,0.00005034893,0.000426235,0.000182197,0.00016975,0.0001754739],"domain_scores_gemma":[0.9985624,0.0003921135,0.0002411699,0.0001203952,0.0005475875,0.0001363553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001181509,0.001815902,0.05441117,0.000005288578,0.000453518,0.003247276,0.00008514778,0.000001787551,0.09107549,0.003602184,0.001649027,0.8424717],"study_design_scores_gemma":[0.02376759,0.01294465,0.8891517,0.0001817836,0.0003865891,0.01136538,0.00008521423,0.0003052553,0.0201972,0.01311899,0.02812828,0.0003673583],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9098431,0.000340599,0.07269365,0.01413147,0.002140079,0.000258064,0.00005682236,0.00002050685,0.0005156389],"genre_scores_gemma":[0.9619647,0.00006949963,0.03605556,0.001027927,0.0007742621,0.0000254533,0.000009316476,0.00001073798,0.00006256831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8421043,"threshold_uncertainty_score":0.5619697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193803236188791,"score_gpt":0.3277084716529505,"score_spread":0.3057704392910626,"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."}}