{"id":"W2118854406","doi":"10.1177/193229681200600321","title":"Analysis of an Electrochemical Blood Glucose Monitoring System with Hematocrit Compensation: Improved Accuracy by Design","year":2012,"lang":"en","type":"letter","venue":"Journal of Diabetes Science and Technology","topic":"Diabetes Management and Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of Calgary","funders":"","keywords":"Hematocrit; Glucose meter; Medicine; Compensation (psychology); Diabetes mellitus; Blood glucose monitoring; Internal medicine; Psychology; Endocrinology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001395014,0.0002222814,0.001003619,0.002751533,0.0001128283,0.00007360544,0.0006327103,0.0003872911,0.000007477968],"category_scores_gemma":[0.0002985288,0.0001498861,0.0000951473,0.00328645,0.0009355483,0.0004001369,0.0001236025,0.001219329,6.569969e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001163577,"about_ca_system_score_gemma":0.0002887272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001270925,"about_ca_topic_score_gemma":1.234642e-7,"domain_scores_codex":[0.9974011,0.00004778988,0.0005401017,0.0003119815,0.001031389,0.0006676121],"domain_scores_gemma":[0.9973385,0.000190886,0.0007328633,0.0004033532,0.00118111,0.0001532874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005248176,0.0003422669,0.08126336,0.0009306248,0.003223333,0.0001031084,0.00004423036,0.000001375725,0.9029821,0.00003031524,0.002948672,0.008078157],"study_design_scores_gemma":[0.002132729,0.004998329,0.002184969,0.001027119,0.009811355,0.0001038,0.0003578036,0.003254696,0.9734491,0.00005187387,0.002197182,0.000431023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690239,0.002547928,0.00023838,0.02765198,0.00008688375,0.0003615709,0.000003205765,0.00004027012,0.00004584688],"genre_scores_gemma":[0.9953206,0.00005343216,0.002796359,0.001374313,0.0003658454,0.00001387902,0.00001012469,0.00002124564,0.00004426492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07907838,"threshold_uncertainty_score":0.6112176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486304791608271,"score_gpt":0.2726373192860631,"score_spread":0.2577742713699803,"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."}}