{"id":"W2896927272","doi":"10.2196/10212","title":"Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study","year":2018,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Computer science; Artificial intelligence; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.004800408,0.000860314,0.0008132011,0.0005400587,0.0002594957,0.0003609978,0.0005802446,0.0006963056,0.001330246],"category_scores_gemma":[0.00853963,0.0002511954,0.0008015033,0.0003692625,0.0003200223,0.0006410225,0.0003864086,0.0008541986,0.0004008273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003259239,"about_ca_system_score_gemma":0.000550156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003033969,"about_ca_topic_score_gemma":0.00123479,"domain_scores_codex":[0.9989586,0.000705514,0.00005229993,0.0001352128,0.00007204462,0.00007636262],"domain_scores_gemma":[0.9914916,0.006161171,0.0002636831,0.0006469821,0.001056986,0.0003795356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02146497,0.04025804,0.6122223,0.0003271855,0.001082845,0.0008911077,0.0006351568,0.0824677,0.007134486,0.0003879136,0.002645,0.2304832],"study_design_scores_gemma":[0.002689579,0.05428022,0.2164247,0.00003891178,0.0003716578,0.0004590233,0.0002825201,0.7209674,0.003244425,0.0004516233,0.0007219219,0.0000680596],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945205,0.00008900839,0.004661525,0.00008095639,0.00001505998,0.0002242809,0.0001289739,0.00007299835,0.0002068114],"genre_scores_gemma":[0.9883051,0.00009825862,0.01064393,0.00004668542,0.00003098409,0.0002324676,0.0003744647,0.00000868854,0.0002593764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004800408,"threshold_uncertainty_score":0.02538729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1394892210532136,"score_gpt":0.4368438856149038,"score_spread":0.2973546645616902,"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."}}