{"id":"W3198518576","doi":"10.1016/j.ebiom.2021.103563","title":"A holistic approach to predicting diabetes risk via biomarkers","year":2021,"lang":"en","type":"letter","venue":"EBioMedicine","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Centre Hospitalier Universitaire de Sherbrooke","funders":"","keywords":"Mahalanobis distance; Context (archaeology); Operationalization; Psychology; Medicine; Bioinformatics; Epistemology; Biology; Philosophy; Artificial intelligence; Computer science","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":[0.003003756,0.001672134,0.001848341,0.004862103,0.0007066692,0.004872409,0.001355821,0.001707045,0.002865948],"category_scores_gemma":[0.00762908,0.0005784362,0.001423896,0.003119498,0.001280286,0.002545534,0.00272681,0.002956494,0.00113372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009196969,"about_ca_system_score_gemma":0.00134085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003261625,"about_ca_topic_score_gemma":0.002892458,"domain_scores_codex":[0.9984748,0.00067389,0.0001104559,0.0003699505,0.000290529,0.00008036936],"domain_scores_gemma":[0.9982865,0.0007414641,0.0002962946,0.0001952936,0.000311634,0.0001687173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009891314,0.0004630751,0.2178329,0.001265069,0.002944674,0.0009728703,0.0009628891,0.02470207,0.005659305,0.05031709,0.02630139,0.6675896],"study_design_scores_gemma":[0.0001486613,0.001970708,0.1471418,0.002976481,0.003055158,0.00378904,0.002268528,0.2107323,0.005973009,0.542277,0.07902146,0.0006459315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.1099709,0.1045295,0.6654059,0.07003545,0.003032744,0.0004122796,0.007951935,0.001937925,0.03672346],"genre_scores_gemma":[0.7308775,0.03109974,0.2198062,0.008833813,0.002742377,0.0003620832,0.001849322,0.0001129789,0.004315994],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.004872409,"threshold_uncertainty_score":0.01588559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03983297852434442,"score_gpt":0.2776391257056004,"score_spread":0.237806147181256,"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."}}