{"id":"W6930739150","doi":"10.5281/zenodo.13287011","title":"Performance of Machine Learning Classifiers for Diabetes Prediction","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"C4.5 algorithm; Decision tree; Perceptron; Logistic regression; Stochastic gradient descent; Multilayer perceptron; Receiver operating characteristic; Random forest","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":[0.01179166,0.001991612,0.002223199,0.004117376,0.0007438542,0.002640127,0.001296265,0.002066262,0.001075318],"category_scores_gemma":[0.03181044,0.0004066477,0.001212339,0.002676367,0.0003558173,0.002039759,0.0007443917,0.001623386,0.001253851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001107977,"about_ca_system_score_gemma":0.001326185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006481931,"about_ca_topic_score_gemma":0.002870229,"domain_scores_codex":[0.9932228,0.002331486,0.0008452475,0.001124144,0.00198919,0.0004870915],"domain_scores_gemma":[0.9758169,0.01765402,0.001198066,0.001233036,0.003733485,0.000364453],"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":[0.001895431,0.0005753179,0.09328987,0.0005252373,0.0008773713,0.0003214725,0.0001250128,0.3117668,0.003511231,0.001552097,0.01153034,0.5740298],"study_design_scores_gemma":[0.00002686138,0.000280153,0.008664394,0.00009085615,0.0001076789,0.0001095617,0.00006615973,0.9842011,0.003630461,0.001267844,0.00151707,0.00003787599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5821603,0.02658978,0.3595484,0.002873245,0.002270336,0.0005666987,0.00552506,0.007491328,0.01297492],"genre_scores_gemma":[0.9133465,0.002064325,0.07890481,0.0003559401,0.0003356191,0.0001423078,0.003483546,0.0001046435,0.001262321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01179166,"threshold_uncertainty_score":0.062361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1226780137013686,"score_gpt":0.3776898750445135,"score_spread":0.2550118613431449,"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."}}