{"id":"W2547447314","doi":"10.32920/ryerson.14660673","title":"Comparative analysis of classification models for diagnosis Type 2 Diabetes","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Hospital for Sick Children; McMaster University","keywords":"C4.5 algorithm; Machine learning; Computer science; Decision tree; Artificial intelligence; Data mining; Medical diagnosis; Expert system; Multilayer perceptron; Support vector machine; Perceptron; Naive Bayes classifier; Artificial neural network; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007318919,0.0002415152,0.001311668,0.0004403157,0.0003213315,0.0000142343,0.000338929,0.0007207345,0.001196411],"category_scores_gemma":[0.0004974167,0.0002254589,0.0003885004,0.000967894,0.0000850218,0.00009104047,0.0003653968,0.0007815273,0.00002613897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002803246,"about_ca_system_score_gemma":0.0009144257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486288,"about_ca_topic_score_gemma":0.01033909,"domain_scores_codex":[0.9965825,0.0006766795,0.00140872,0.000630583,0.0002726405,0.0004288868],"domain_scores_gemma":[0.9915307,0.003566341,0.0009165932,0.0008494454,0.003013688,0.0001232723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009532117,0.0003552886,0.8215572,0.003717803,0.004390722,4.11879e-7,0.03599487,0.09195308,0.0002251863,0.0308281,0.008106183,0.002775792],"study_design_scores_gemma":[0.00004311804,0.00005607666,0.01539455,0.0004770354,0.00157302,3.706235e-9,0.02465864,0.9467991,0.0020596,0.008261503,0.0004139434,0.0002634112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718587,0.001256779,0.01473495,0.001581937,0.001632717,0.003225355,0.0005173908,0.0001091723,0.005082967],"genre_scores_gemma":[0.9898528,0.0005358694,0.004247237,0.000374024,0.0001491294,0.002810454,0.001579224,0.00002161995,0.0004295826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.854846,"threshold_uncertainty_score":0.9997166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5582518129913863,"score_gpt":0.567110148366119,"score_spread":0.008858335374732684,"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."}}