{"id":"W4236483910","doi":"10.1002/0471463736.tnmp32","title":"Uterine Cervix Cancer","year":2003,"lang":"en","type":"other","venue":"TNM Online","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Multivariate analysis; Multivariate statistics; Medicine; Cervix; Proportional hazards model; Univariate; Oncology; Cancer; Internal medicine; Uterine cervix; Univariate analysis; Carcinoma; Gynecology; 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":[0.00009788849,0.0002780426,0.0002195155,0.0007962195,0.0002854194,0.0003952323,0.0002261461,0.0002890076,0.08517452],"category_scores_gemma":[0.000378165,0.00004644808,0.0002341845,0.001138989,0.00009478871,0.0001313703,0.0002828298,0.0002351096,0.01768021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005133048,"about_ca_system_score_gemma":0.0006560908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004650596,"about_ca_topic_score_gemma":0.00856667,"domain_scores_codex":[0.9999185,0.00001805954,0.000006014341,0.000010069,0.00002873778,0.00001872923],"domain_scores_gemma":[0.9999194,0.00001551149,0.00001406383,0.000007157951,0.000022917,0.00002099121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001288154,0.00006826044,0.005648688,0.001136878,0.00001887284,0.0009081394,0.00004516182,0.0001423449,0.001138352,0.002053471,0.1415744,0.8471365],"study_design_scores_gemma":[0.00001964222,0.000076805,0.0127684,0.0005276159,0.0000183831,0.002924504,0.00004770168,0.00004629199,0.0006061646,0.0004546278,0.9825067,0.000003254342],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01253346,0.1532856,0.0005931734,0.00298963,0.001074053,0.0002232602,0.006569463,0.0001982016,0.8225331],"genre_scores_gemma":[0.1226757,0.1798317,0.002041168,0.003754839,0.001022192,0.0002975966,0.01118969,0.0000575796,0.6791295],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08517452,"threshold_uncertainty_score":0.2849371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03668198860755976,"score_gpt":0.3682768062501248,"score_spread":0.331594817642565,"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."}}