{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01144503,0.0008883854,0.0009146106,0.00100009,0.0003191439,0.001043146,0.001002751,0.000943035,0.0006597281],"category_scores_gemma":[0.0259032,0.0003529667,0.0008317877,0.000681015,0.000329836,0.0006906994,0.0008437535,0.001509382,0.0002986288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008841467,"about_ca_system_score_gemma":0.002088723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01318005,"about_ca_topic_score_gemma":0.004944165,"domain_scores_codex":[0.9978861,0.001124791,0.0001766785,0.0003835735,0.0003125693,0.0001161941],"domain_scores_gemma":[0.9857621,0.01080069,0.0006487701,0.0006771674,0.001893685,0.0002174968],"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":[0.0007568006,0.0004556262,0.1686133,0.0001078628,0.0006181862,0.0001830201,0.0001277672,0.7533745,0.001401266,0.001011983,0.001543951,0.07180578],"study_design_scores_gemma":[0.00002600446,0.0001450697,0.007280184,0.00002394955,0.00003882738,0.0000289623,0.0000180011,0.9912975,0.0004338209,0.0005377083,0.0001613712,0.000008691664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.798957,0.0006039652,0.1965039,0.0006978135,0.00008790084,0.000366278,0.0009303524,0.0003923358,0.001460448],"genre_scores_gemma":[0.9509174,0.0001543146,0.04722671,0.00008490775,0.00002550018,0.0001662042,0.001025046,0.00001543572,0.0003845491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01318005,"threshold_uncertainty_score":0.0605278,"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."}}