{"id":"W3122074426","doi":"10.1177/1460458220977584","title":"The challenge of predicting blood glucose concentration changes in patients with type I diabetes","year":2021,"lang":"en","type":"article","venue":"Health Informatics Journal","topic":"Diabetes Management and Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Diabetes Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Machine Intelligence Institute","keywords":"Type 2 diabetes; Diabetes mellitus; Medicine; Internal medicine; Endocrinology; Cardiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003204195,0.0008257472,0.0009277671,0.0005945765,0.0003581391,0.001429174,0.0007624955,0.000918544,0.0003227653],"category_scores_gemma":[0.01278296,0.0002846075,0.0006064025,0.001017444,0.0002666413,0.0008303809,0.0007131277,0.002074616,0.0003908285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005306494,"about_ca_system_score_gemma":0.0009167804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01168254,"about_ca_topic_score_gemma":0.008807728,"domain_scores_codex":[0.9988214,0.0005471322,0.0001099492,0.000275422,0.0001704351,0.00007565528],"domain_scores_gemma":[0.9954948,0.002973196,0.0003749974,0.0004822442,0.0004866187,0.0001880259],"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":[0.0007514995,0.0007114891,0.4529297,0.0001622071,0.0003563505,0.0004639928,0.0003318976,0.2713906,0.003150427,0.0006033317,0.01160614,0.2575425],"study_design_scores_gemma":[0.00003696562,0.0003186117,0.06619856,0.00005564968,0.00008742233,0.0003115001,0.0003503859,0.9246101,0.003002548,0.002557372,0.002426035,0.00004492527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9154544,0.002556696,0.06932281,0.005889286,0.0003215697,0.00009431088,0.002946742,0.0007889526,0.002625213],"genre_scores_gemma":[0.9718545,0.0006345275,0.02467457,0.0004881436,0.0001335968,0.00002815565,0.001797421,0.00003345525,0.0003556664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01168254,"threshold_uncertainty_score":0.02322906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128955771810886,"score_gpt":0.2888752681187652,"score_spread":0.2675857104006564,"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."}}