{"id":"W4411715903","doi":"10.1097/01.cot.0000000000000080","title":"Cervical Cancer Incidence & Mortality Expected to Soar by 2050","year":2025,"lang":"en","type":"article","venue":"Oncology Times","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soar; Cervical cancer; Incidence (geometry); Medicine; Oncology; Cancer; Internal medicine; Demography; Computer science; Artificial intelligence; Mathematics; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008820868,0.0005442949,0.0004112549,0.002170891,0.0005149409,0.001320366,0.000532714,0.0009666125,0.02844642],"category_scores_gemma":[0.003712016,0.0001711213,0.001145478,0.002199406,0.0003027297,0.001116646,0.0008908215,0.002041705,0.01618251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252207,"about_ca_system_score_gemma":0.002446025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01860621,"about_ca_topic_score_gemma":0.01621916,"domain_scores_codex":[0.9991364,0.0001222528,0.00006342446,0.0001127339,0.0004282979,0.000136866],"domain_scores_gemma":[0.9989409,0.0001036971,0.0002777419,0.00003169108,0.0004035926,0.0002424665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001347623,0.00003873225,0.04486247,0.001808693,0.0001826624,0.0001417722,0.0001616885,0.001129154,0.0003731071,0.01117093,0.6971674,0.2428286],"study_design_scores_gemma":[0.00003488377,0.0001372046,0.1079524,0.001472021,0.0002019493,0.0008831488,0.0004508057,0.001459479,0.0004510429,0.004596857,0.8823202,0.00004005498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04557629,0.1713591,0.01183147,0.1039084,0.01934998,0.0005735839,0.3167195,0.005498355,0.3251833],"genre_scores_gemma":[0.5499431,0.1578176,0.009333402,0.02798528,0.008768099,0.001422604,0.1440346,0.000559655,0.1001356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02844642,"threshold_uncertainty_score":0.09516269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04452170050135746,"score_gpt":0.4467629008338472,"score_spread":0.4022412003324897,"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."}}