{"id":"W2113308910","doi":"10.1177/014572170002600610","title":"Identifying Variables Associated With Inaccurate Self-Monitoring of Blood Glucose: Proposed Guidelines to Improve Accuracy","year":2000,"lang":"en","type":"article","venue":"The Diabetes Educator","topic":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Capital District Health Authority","funders":"","keywords":"Blood Glucose Self-Monitoring; Self-monitoring; Continuous glucose monitoring; Computer science; Medicine; Psychology; Diabetes mellitus; Social 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":[0.000385398,0.0002617663,0.0005136397,0.0000816633,0.0001746872,0.00005715709,0.0002739261,0.0001051296,0.0002465105],"category_scores_gemma":[0.001222665,0.0001618382,0.0001119203,0.0004177257,0.0000805186,0.0001302212,0.00004585813,0.0002272668,0.0000353127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005518904,"about_ca_system_score_gemma":0.0003309239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005641274,"about_ca_topic_score_gemma":0.00000168866,"domain_scores_codex":[0.9980737,0.00006970564,0.0005766355,0.0003369935,0.0004029431,0.0005399985],"domain_scores_gemma":[0.9981211,0.0004355833,0.0001419908,0.0004941351,0.0005588916,0.0002482518],"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":[0.001476879,0.00387335,0.5438861,0.0008244537,0.003638172,0.00003747027,0.007095159,0.00002594519,0.389235,0.0003139947,0.001770766,0.04782276],"study_design_scores_gemma":[0.02390374,0.006750218,0.1365899,0.007431828,0.009421036,0.0000360638,0.004575829,0.0005279293,0.7962569,0.001202763,0.01124727,0.002056559],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956924,0.0007852064,0.000003546234,0.001471404,0.0004556763,0.0007833896,0.00002898922,0.0001072533,0.0006721823],"genre_scores_gemma":[0.9961572,0.00009346585,0.001785734,0.0005579317,0.0004440513,0.0001002776,0.00002052388,0.00004273318,0.0007980326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4072962,"threshold_uncertainty_score":0.6599569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235286042331118,"score_gpt":0.3077480208432322,"score_spread":0.285395160419921,"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."}}