{"id":"W3012372916","doi":"10.21203/rs.3.rs-24189/v1","title":"Challenges of False Positive and Negative Results in Cervical Cancer Screening","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cervical cancer; Cervical cancer screening; Medicine; Cancer; Internal medicine","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":[0.04743713,0.001250277,0.001842096,0.001840998,0.001432513,0.007237747,0.003496692,0.007379484,0.003502751],"category_scores_gemma":[0.172207,0.001667226,0.00257517,0.001544637,0.003513755,0.004457313,0.003040616,0.003633688,0.0009143148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008449693,"about_ca_system_score_gemma":0.005594937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02797531,"about_ca_topic_score_gemma":0.01651092,"domain_scores_codex":[0.9590975,0.03095946,0.001178555,0.002975716,0.004417951,0.001370821],"domain_scores_gemma":[0.7326145,0.2443597,0.01046241,0.003204586,0.008151338,0.001207431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0009955132,0.0002344285,0.0858435,0.002496641,0.0007523483,0.002958887,0.002001668,0.6931795,0.001149475,0.04432521,0.01896708,0.1470957],"study_design_scores_gemma":[0.0001784364,0.000820214,0.02636526,0.002338504,0.0005876165,0.004347385,0.001461043,0.8151463,0.00215853,0.1305587,0.01564773,0.0003903021],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3642766,0.05061158,0.3838485,0.1340593,0.003393201,0.001089959,0.004422128,0.002113791,0.05618494],"genre_scores_gemma":[0.9630098,0.004137321,0.02598233,0.003330933,0.0003649413,0.0002530405,0.0003913091,0.0001092422,0.00242108],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04743713,"threshold_uncertainty_score":0.2508745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1323250287610134,"score_gpt":0.404155714675639,"score_spread":0.2718306859146256,"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."}}