{"id":"W4323045941","doi":"10.21203/rs.3.rs-2526701/v1","title":"Reproducible and Clinically Translatable Deep Neural Networks for Cancer Screening","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Overfitting; Triage; Software portability; Artificial intelligence; Machine learning; Computer science; Deep learning; Cervical cancer; Receiver operating characteristic; Medicine; Population; Visual inspection; Cancer; Artificial neural network; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006340346,0.0003151004,0.0008693957,0.0004614298,0.0004103883,0.0002438945,0.0004227028,0.0006135876,0.001008389],"category_scores_gemma":[0.0020973,0.0002771104,0.0003542524,0.0007297366,0.0003681105,0.00007359251,0.001208398,0.003944007,0.00001361998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001777069,"about_ca_system_score_gemma":0.0006016146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002355459,"about_ca_topic_score_gemma":0.001265202,"domain_scores_codex":[0.9941837,0.0003159813,0.0006805474,0.001811102,0.001502175,0.001506512],"domain_scores_gemma":[0.9944467,0.001667541,0.00007851868,0.001371926,0.001688982,0.0007463315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007588746,0.0002462635,0.0570185,0.01353365,0.000518012,0.0001693719,0.0005824803,0.01263211,0.00005217478,0.0001478007,0.01480903,0.8927019],"study_design_scores_gemma":[0.005132978,0.002231112,0.1668106,0.001515273,0.000229076,0.00001622863,0.0005824036,0.790728,0.0001071387,0.003285885,0.02865373,0.0007075823],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1327381,0.3129566,0.1849444,0.252078,0.006727802,0.07404362,0.003718188,0.003622633,0.02917068],"genre_scores_gemma":[0.9561923,0.01905983,0.003357939,0.0004037499,0.006207354,0.004568362,0.0009208668,0.0003459751,0.0089437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8919943,"threshold_uncertainty_score":0.9999681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3035939631796585,"score_gpt":0.5295118604188808,"score_spread":0.2259178972392223,"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."}}