{"id":"W2213562886","doi":"10.1089/dia.2013.0287","title":"Target Attainment Through Algorithm Design During Intravenous Insulin Infusion","year":2013,"lang":"en","type":"article","venue":"Diabetes Technology & Therapeutics","topic":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Care Foundation","funders":"","keywords":"Medicine; Glycemic; Diabetic ketoacidosis; Insulin; Inflection point; Algorithm; Diabetes mellitus; Multiplicative function; Anesthesia; Internal medicine; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01354951,0.001079813,0.001108984,0.000750226,0.0004511508,0.001634101,0.001395744,0.0009177366,0.001099721],"category_scores_gemma":[0.03001015,0.0006225847,0.0005088469,0.0004116734,0.0008030549,0.001496648,0.001224629,0.001459427,0.0003331095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401022,"about_ca_system_score_gemma":0.002620198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001615347,"about_ca_topic_score_gemma":0.0008221348,"domain_scores_codex":[0.9942819,0.003710896,0.0003271617,0.0007148111,0.0006168045,0.0003484638],"domain_scores_gemma":[0.9774411,0.01652225,0.001770608,0.0008428773,0.003070873,0.0003522578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001350788,0.0003210503,0.00606405,0.0001262169,0.00009330053,0.0000576174,0.0002931522,0.8603902,0.002298516,0.005501289,0.0005037859,0.123],"study_design_scores_gemma":[0.0001016451,0.0002554202,0.0003169453,0.00001024006,0.00001743098,0.00002179429,0.00001240074,0.9960915,0.001391582,0.001517394,0.0002575185,0.000006189825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04397272,0.00008159297,0.9540906,0.00007669761,0.00001361345,0.0003865153,0.00002045641,0.0006173397,0.0007404053],"genre_scores_gemma":[0.6098667,0.00007208801,0.3884852,0.00008213613,0.0000282172,0.0008028592,0.0001152258,0.00009709239,0.0004504648],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01354951,"threshold_uncertainty_score":0.07165748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445691397315458,"score_gpt":0.2521083230645685,"score_spread":0.237651409091414,"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."}}