{"id":"W4312139847","doi":"10.1136/ijgc-2022-igcs.236","title":"EP145/#106 Application of machine learning in endometrial cancer: a systematic review","year":2022,"lang":"en","type":"review","venue":"International Journal of Gynecological Cancer","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Endometrial cancer; Machine learning; Mean absolute error; Medicine; Artificial intelligence; Biomarker; Cancer; Systematic review; Algorithm; Internal medicine; Computer science; Mean squared error; MEDLINE; Statistics; Mathematics","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":[0.00621693,0.001486448,0.009396384,0.004737086,0.0004748325,0.002556154,0.001648729,0.001901907,0.008040905],"category_scores_gemma":[0.02510276,0.000914666,0.00916414,0.006562032,0.0006549653,0.002269959,0.001403549,0.001539045,0.0005479638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001960356,"about_ca_system_score_gemma":0.006738767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007799742,"about_ca_topic_score_gemma":0.02678247,"domain_scores_codex":[0.9960375,0.001440055,0.001368975,0.0003670549,0.0006448129,0.0001415702],"domain_scores_gemma":[0.9857254,0.01109254,0.002039106,0.0002120016,0.0007744457,0.000156391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0003486212,0.00002178549,0.0008494945,0.9343203,0.03284207,0.00007244897,0.00006691883,0.0001126272,0.000139948,0.0001311818,0.001416719,0.02967788],"study_design_scores_gemma":[0.001335153,0.0003514284,0.005958857,0.6100811,0.367289,0.0002791439,0.0001762018,0.0002442909,0.0001853873,0.0004061968,0.01363264,0.00006054984],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006680617,0.9982607,0.0001543779,0.0001278855,0.0000894974,0.0002172332,0.000293673,0.000009492599,0.0001792525],"genre_scores_gemma":[0.01509122,0.982916,0.0007146402,0.0005474848,0.0000851361,0.0002743662,0.0002010341,0.000006841259,0.0001632564],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009396384,"threshold_uncertainty_score":0.03287864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07398715233753653,"score_gpt":0.4159809458887163,"score_spread":0.3419937935511798,"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."}}