{"id":"W2994917102","doi":"10.1002/path.5373","title":"Clinicopathological and molecular characterisation of ‘multiple‐classifier’ endometrial carcinomas","year":2019,"lang":"en","type":"article","venue":"The Journal of Pathology","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":402,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia; BC Cancer Agency","funders":"National Institutes of Health; National Cancer Institute; KWF Kankerbestrijding; Academy of Medical Sciences; Cancer Research UK","keywords":"Classifier (UML); Biology; Endometrial cancer; Carcinoma; Cancer research; Pathology; Medicine; Cancer; Genetics; Artificial intelligence; Computer science","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":[0.0005361752,0.0002211461,0.0003136254,0.001042032,0.0002853867,0.0006579658,0.0003019661,0.0003989563,0.001166119],"category_scores_gemma":[0.002195382,0.0002373448,0.0002524602,0.0006188308,0.0003587817,0.0004127867,0.0003730454,0.0002229106,0.0002485102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002589696,"about_ca_system_score_gemma":0.0002033475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008801663,"about_ca_topic_score_gemma":0.001167453,"domain_scores_codex":[0.9995518,0.00005617327,0.0000735383,0.0001229595,0.0001072585,0.00008827652],"domain_scores_gemma":[0.9987516,0.0002809345,0.0004602786,0.0001654347,0.0001586034,0.0001831594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002409094,0.00001530784,0.9878985,0.00001712713,0.00001971736,0.001750011,0.00007235543,0.0001159202,0.00558554,0.00003776,0.0001041218,0.004142747],"study_design_scores_gemma":[0.00001008665,0.0001152279,0.9793583,0.000008010232,0.00002638678,0.01739405,0.0002308285,0.0006969709,0.001268307,0.00008266597,0.0008004978,0.0000086621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992602,0.000188124,0.0001587181,0.00001382133,0.000003064531,0.000006653178,0.0000767521,0.000004078837,0.0002885427],"genre_scores_gemma":[0.9995219,0.00005763939,0.0001746979,0.000006814127,0.000006810074,0.000005700664,0.0001573197,0.000002348785,0.00006699478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001166119,"threshold_uncertainty_score":0.003901005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03472323636634328,"score_gpt":0.2973658092991086,"score_spread":0.2626425729327653,"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."}}