{"id":"W4402491912","doi":"10.2196/60853","title":"Peer Review of “Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals”","year":2024,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Diabetes Management and Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Cohort; Risk assessment; Medicine; Peer assessment; Artificial intelligence; Machine learning; Computer science; Medical education; Internal medicine; Computer security","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03468068,0.0008652683,0.001909305,0.003346943,0.003901529,0.006694357,0.002822891,0.005553242,0.07106748],"category_scores_gemma":[0.2666596,0.0006230596,0.002000856,0.001672044,0.002181731,0.002980653,0.00293398,0.004321665,0.03060308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001993079,"about_ca_system_score_gemma":0.01359472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003139645,"about_ca_topic_score_gemma":0.006560298,"domain_scores_codex":[0.9670705,0.01287726,0.003671789,0.002164423,0.01287107,0.001344984],"domain_scores_gemma":[0.5417964,0.0422883,0.011337,0.0159612,0.3753445,0.01327251],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001905858,0.00003452799,0.0009043388,0.0007670626,0.00006186027,0.0001479548,0.0001079887,0.00005274705,0.0003975066,0.0004692948,0.9644741,0.03239202],"study_design_scores_gemma":[0.0003159471,0.0001329871,0.006740099,0.001997984,0.000172335,0.0005719591,0.0004673225,0.001863142,0.001759718,0.003515105,0.9823703,0.00009304246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"commentary","genre_scores_codex":[0.00751288,0.005240835,0.01136721,0.332155,0.6002629,0.003261005,0.003593218,0.00186944,0.03473752],"genre_scores_gemma":[0.09375501,0.01389599,0.0270355,0.1436771,0.4702068,0.003755997,0.01081566,0.003647575,0.2332104],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9653193,"threshold_uncertainty_score":0.2377444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187534382389143,"score_gpt":0.3509448118666461,"score_spread":0.3321913736277318,"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."}}