{"id":"W1835902352","doi":"10.1002/0471463736.tnmp32.pub2","title":"Uterine Cervix Cancer","year":2006,"lang":"en","type":"other","venue":"TNM Online","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Multivariate analysis; Multivariate statistics; Medicine; Cervix; Proportional hazards model; Oncology; Cancer; Univariate; 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":[0.0001011626,0.000299425,0.0002360001,0.0008390353,0.0002756213,0.0004098164,0.0002204701,0.0002981122,0.07559291],"category_scores_gemma":[0.0003760559,0.00004697801,0.0002505372,0.001148616,0.00009709586,0.000133178,0.0002875863,0.0002426027,0.01660829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004588044,"about_ca_system_score_gemma":0.0006105091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003642029,"about_ca_topic_score_gemma":0.006631887,"domain_scores_codex":[0.9999112,0.00001962933,0.000006824014,0.00001134453,0.0000310801,0.00001992905],"domain_scores_gemma":[0.9999225,0.00001501407,0.00001452945,0.00000650597,0.00002133783,0.00002002994],"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":[0.0001138748,0.00005803703,0.004493975,0.001376886,0.00002112124,0.0008005537,0.00003927015,0.0001423145,0.001079113,0.00202677,0.1325047,0.8573434],"study_design_scores_gemma":[0.00001766384,0.00007640702,0.01035383,0.0006455583,0.00001925369,0.002834668,0.00004188349,0.00004439911,0.0005924168,0.000423982,0.9849464,0.000003499318],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01264879,0.245859,0.0007203317,0.003159582,0.001354985,0.0002332032,0.007212181,0.000214567,0.7285974],"genre_scores_gemma":[0.1262684,0.2613722,0.00247635,0.003903542,0.001236379,0.0003023405,0.01270612,0.00005640693,0.5916783],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07559291,"threshold_uncertainty_score":0.2528834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954092144059136,"score_gpt":0.359155362139347,"score_spread":0.3296144406987557,"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."}}