{"id":"W4410168835","doi":"10.1002/cdt3.70007","title":"Protocol for an Integrative Meta‐Analysis of the Application of Machine Learning Algorithms in the Prediction of Chronic Disease Risks and Outcomes","year":2025,"lang":"en","type":"article","venue":"Chronic Diseases and Translational Medicine","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Medicine; Protocol (science); Disease; Meta-analysis; Machine learning; Algorithm; Artificial intelligence; Alternative medicine; Computer science; Internal medicine; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004666647,0.0001072836,0.0004497703,0.0001598405,0.0002092888,0.000001353717,0.0001163744,0.0000510445,0.0000498696],"category_scores_gemma":[0.0001960782,0.0000525266,0.0001392648,0.0004883076,0.0003312708,0.00006407279,0.00001525282,0.0001846365,4.11175e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000374079,"about_ca_system_score_gemma":0.0004054788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001809186,"about_ca_topic_score_gemma":0.003457027,"domain_scores_codex":[0.9984424,0.0003744896,0.0006552439,0.0001866406,0.0002255916,0.0001156443],"domain_scores_gemma":[0.9978137,0.001456055,0.0003025463,0.0001902262,0.0001859723,0.00005150447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003413694,0.000216825,0.9461782,0.002871887,0.002865335,8.676837e-8,0.003219618,0.002919496,0.00004181935,0.02218666,0.00001247872,0.01914622],"study_design_scores_gemma":[0.0007671203,0.0002356204,0.6885276,0.0002765782,0.01040156,3.114632e-8,0.001293805,0.2915765,0.00001370312,0.006513689,0.0003554195,0.00003835498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"protocol","genre_gemma":"empirical","genre_scores_codex":[0.1964119,0.04522984,0.181587,0.05019842,0.0005370612,0.5169989,0.008338523,0.0001066296,0.0005916869],"genre_scores_gemma":[0.9594046,0.00006108968,0.00003231811,0.00007283653,0.00005036141,0.04023461,0.0001208512,0.000005033617,0.00001829451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7629927,"threshold_uncertainty_score":0.273496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.194950014305824,"score_gpt":0.5247377087847794,"score_spread":0.3297876944789555,"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."}}