{"id":"W2274212597","doi":"10.1177/1932296815599551","title":"Economic Value of Improved Accuracy for Self-Monitoring of Blood Glucose Devices for Type 1 Diabetes in Canada","year":2015,"lang":"en","type":"article","venue":"Journal of Diabetes Science and Technology","topic":"Diabetes Management and Research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bayer (Canada)","funders":"Bayer HealthCare; Public Health Agency of Canada","keywords":"Blood Glucose Self-Monitoring; Type 1 diabetes; Continuous glucose monitoring; Medicine; Diabetes mellitus; Type 2 diabetes; Blood glucose monitoring; Value (mathematics); Intensive care medicine; Emergency medicine; Endocrinology; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001332039,0.00008117579,0.0003948536,0.0006800955,0.0000332098,0.00001262578,0.0003259106,0.00005652961,0.000001028441],"category_scores_gemma":[0.001270903,0.00006242087,0.00003365686,0.0005255308,0.000240561,0.0002173875,0.00009558623,0.0001133121,1.015352e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000158915,"about_ca_system_score_gemma":0.002308714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007253857,"about_ca_topic_score_gemma":0.002277972,"domain_scores_codex":[0.9988776,0.000008165464,0.0004102499,0.0001362173,0.0002176217,0.0003501695],"domain_scores_gemma":[0.9984397,0.0002383644,0.0003582696,0.0001366897,0.0007245109,0.0001025216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002371502,0.00007983527,0.8916421,0.0002770232,0.00008836322,7.770035e-7,0.00002656555,0.000008460807,0.09337879,0.0001938289,0.00005625677,0.01422431],"study_design_scores_gemma":[0.004734228,0.004654088,0.08408005,0.0004206038,0.0002941231,0.000001725229,0.0013788,0.007080408,0.8936108,0.002407017,0.001173491,0.0001646109],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967097,0.001848703,0.000001133992,0.000814559,0.0002703555,0.0003136741,0.000003933839,0.000005246032,0.00003267012],"genre_scores_gemma":[0.9967764,0.00006743369,0.003058209,0.00001937525,0.00005381081,0.000009585247,3.960143e-7,0.000006707878,0.000008075921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8075621,"threshold_uncertainty_score":0.409556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308698983043917,"score_gpt":0.3042659434310598,"score_spread":0.2811789536006206,"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."}}