{"id":"W4313450375","doi":"10.1101/2022.12.17.22282984","title":"Reproducible And Clinically Translatable Deep Neural Networks For Cervical Screening","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Triage; Overfitting; Software portability; Artificial intelligence; Computer science; Machine learning; Receiver operating characteristic; Medicine; Deep learning; Cervical cancer; Population; Visual inspection; Artificial neural network; Cancer; Medical emergency; 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":[0.002100613,0.001128394,0.0004859971,0.0004827413,0.0002616607,0.0007954774,0.001613651,0.00110932,0.001807656],"category_scores_gemma":[0.00703772,0.0003687931,0.0005638349,0.0004116968,0.0004896953,0.0006823136,0.001155079,0.0015721,0.0007250637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173757,"about_ca_system_score_gemma":0.00164335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007939666,"about_ca_topic_score_gemma":0.01011214,"domain_scores_codex":[0.9992061,0.0003003998,0.00003989407,0.0002073942,0.0001571736,0.00008896262],"domain_scores_gemma":[0.9988139,0.0005254481,0.0001151159,0.000202315,0.0002793469,0.00006396932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004725147,0.0004397525,0.01384497,0.0002834651,0.000238236,0.0002340163,0.00007655962,0.7173528,0.01317233,0.00205494,0.01597796,0.2358525],"study_design_scores_gemma":[0.00003259395,0.0001017172,0.00110936,0.00003264851,0.00002214348,0.00003552297,0.00001915697,0.9899105,0.005212915,0.002137283,0.001374799,0.00001128772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4106817,0.00517761,0.5539625,0.005263481,0.0007049625,0.0005658476,0.005348136,0.01093985,0.007355932],"genre_scores_gemma":[0.8769963,0.0005742649,0.1131723,0.001030275,0.0001006051,0.0003391301,0.004127259,0.0002566347,0.003403332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007939666,"threshold_uncertainty_score":0.01578689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0955837091905722,"score_gpt":0.3926963251423379,"score_spread":0.2971126159517657,"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."}}