{"id":"W3000308030","doi":"10.1002/dmrr.3252","title":"Prediction of progression from pre‐diabetes to diabetes: Development and validation of a machine learning model","year":2020,"lang":"en","type":"article","venue":"Diabetes/Metabolism Research and Reviews","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logistic regression; Machine learning; Artificial intelligence; Diabetes mellitus; Medicine; Data set; Cohort; Predictive modelling; Computer science; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002745491,0.0002321103,0.0007399655,0.0002835074,0.000231705,0.00009661252,0.0005393751,0.0001103098,0.00001110034],"category_scores_gemma":[0.00162508,0.0001813241,0.00005843591,0.0009085295,0.0001141642,0.0003557253,0.0007912125,0.0006127659,0.000009170021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000211554,"about_ca_system_score_gemma":0.0001100546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002172114,"about_ca_topic_score_gemma":0.000001373548,"domain_scores_codex":[0.996155,0.0009693995,0.000833703,0.0006950086,0.0007809349,0.0005659911],"domain_scores_gemma":[0.9981397,0.0003325474,0.0003094048,0.000393859,0.0003485813,0.0004758602],"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":[0.00002423035,0.0001264077,0.3914981,0.003273299,0.00005973005,6.091453e-7,0.008671128,0.0006930546,0.06130703,0.0004720261,0.0003362719,0.5335381],"study_design_scores_gemma":[0.0007214262,0.0008353291,0.05496054,0.001717246,0.00002851312,1.368779e-7,0.00003583202,0.7598132,0.1625987,0.000794391,0.01814465,0.0003500008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515104,0.04161182,0.004228431,0.001239259,0.00005796289,0.00121876,0.0000309096,0.00005964852,0.00004275062],"genre_scores_gemma":[0.9299651,0.00227242,0.06707425,0.0002024888,0.0001012726,0.0002527911,0.00006989997,0.00002502135,0.00003675441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7591202,"threshold_uncertainty_score":0.7394184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088876654262294,"score_gpt":0.3605095128522478,"score_spread":0.2516218474260184,"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."}}