{"id":"W2792804309","doi":"10.1097/pgp.0000000000000481","title":"Canadian Consensus-based and Evidence-based Guidelines for Benign Endometrial Pathology Reporting in Biopsy Material","year":2018,"lang":"en","type":"article","venue":"International Journal of Gynecological Pathology","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre hospitalier universitaire de Québec; University of Calgary; Vancouver General Hospital; University Health Network; Health Sciences Centre; University of Saskatchewan; Trillium Health Centre; Saskatoon City Hospital; Sunnybrook Health Science Centre; University of British Columbia; University of Toronto; Memorial University of Newfoundland","funders":"","keywords":"Guideline; Terminology; Medicine; Endometrial biopsy; Critical appraisal; Endometrial cancer; Biopsy; Medical diagnosis; MEDLINE; Gynecology; Standardization; Medical physics; Pathology; Cancer; Internal medicine; Alternative medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002147136,0.0001666137,0.0006612579,0.0008885089,0.0000555496,0.00002769308,0.0001857551,0.0002665299,0.0005025006],"category_scores_gemma":[0.05000813,0.000118537,0.0001933277,0.0002300464,0.0002695506,0.00005094537,0.00003525628,0.0001961398,0.000004769173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004471396,"about_ca_system_score_gemma":0.0008373741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001292508,"about_ca_topic_score_gemma":0.003203207,"domain_scores_codex":[0.9971502,0.000192234,0.001744554,0.0002926893,0.0002921372,0.0003281197],"domain_scores_gemma":[0.9944993,0.001866588,0.001210628,0.0001095379,0.002050801,0.0002632053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03374699,0.0009198562,0.7967088,0.00007791934,0.0003628698,0.04498738,0.000100957,0.0001038365,0.05856336,0.0009037218,0.001520197,0.06200416],"study_design_scores_gemma":[0.05854565,0.02959487,0.8474048,0.0009949746,0.0004970851,0.01680965,0.0001752806,0.001161837,0.02515968,0.01176477,0.00720347,0.0006879326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745729,0.0003044419,0.0004970243,0.02111994,0.002941169,0.0003449553,0.00005547519,0.0000109733,0.0001531007],"genre_scores_gemma":[0.9766195,0.00003686119,0.01696209,0.004747275,0.001561783,0.00002544395,0.00001800017,0.00001159024,0.00001741936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06131623,"threshold_uncertainty_score":0.957994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1703312345013156,"score_gpt":0.4188455128953095,"score_spread":0.2485142783939939,"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."}}