{"id":"W2612695387","doi":"10.1148/radiol.2017161950","title":"Endometrial Carcinoma: MR Imaging–based Texture Model for Preoperative Risk Stratification—A Preliminary Analysis","year":2017,"lang":"en","type":"article","venue":"Radiology","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Medicine; Receiver operating characteristic; Random forest; Magnetic resonance imaging; Radiology; Carcinoma; Risk stratification; Nuclear medicine; Artificial intelligence; Internal medicine; 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":[0.002518764,0.0005592789,0.0005590509,0.0009034451,0.0002129958,0.000610962,0.0003636521,0.0003226459,0.0005561194],"category_scores_gemma":[0.007042893,0.0001738635,0.0009048501,0.000384397,0.0001833862,0.000323908,0.0002881212,0.0002570057,0.0001606132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003913958,"about_ca_system_score_gemma":0.0005481565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004748072,"about_ca_topic_score_gemma":0.002322088,"domain_scores_codex":[0.9995882,0.0001977979,0.00002313796,0.00007862799,0.00006580375,0.00004655117],"domain_scores_gemma":[0.9977461,0.001607235,0.0002040871,0.0001331708,0.000250048,0.00005938084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00260468,0.0003797645,0.503148,0.0001141907,0.0005860147,0.0004177823,0.000135382,0.3626392,0.009121691,0.001102395,0.0008244632,0.1189264],"study_design_scores_gemma":[0.00002558064,0.0002103765,0.04070207,0.000009994113,0.00008818904,0.0001745823,0.00002170255,0.9575434,0.0005722667,0.0004863907,0.0001496848,0.00001573718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963125,0.0004695136,0.1020287,0.0001984888,0.0000151393,0.00009797602,0.000303638,0.0001751754,0.0003988678],"genre_scores_gemma":[0.9869703,0.00009592059,0.01246649,0.00001553299,0.00001684719,0.00004181957,0.0002650671,0.000009465145,0.0001185646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004748072,"threshold_uncertainty_score":0.01332062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03619305623974698,"score_gpt":0.3292563810060423,"score_spread":0.2930633247662953,"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."}}