{"id":"W3155043239","doi":"10.5430/air.v10n1p43","title":"Development process of multiagent system for glycemic control of intensive care unit patients","year":2021,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glycemic; Intensive care unit; Process (computing); Medicine; Health care; Intensive care medicine; Control (management); Inference; Computer science; Risk analysis (engineering); Process management; Engineering; Artificial intelligence; Diabetes mellitus","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000912759,0.0003640576,0.0003136162,0.0003623534,0.0005614958,0.0009534037,0.0007164658,0.000466087,0.002903143],"category_scores_gemma":[0.001473717,0.0002171697,0.0004081303,0.0001639308,0.0001927576,0.0004498968,0.0007571512,0.0005136,0.0007899805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003115076,"about_ca_system_score_gemma":0.001571888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001598462,"about_ca_topic_score_gemma":0.001167385,"domain_scores_codex":[0.9994729,0.0001576823,0.00004205376,0.000101092,0.0001748888,0.00005136706],"domain_scores_gemma":[0.9996099,0.00008871807,0.00003597487,0.00004160024,0.0001632434,0.00006057876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006313209,0.001045095,0.01577317,0.001130767,0.000214935,0.002924592,0.003924181,0.1749838,0.1404469,0.03067691,0.01484419,0.6134041],"study_design_scores_gemma":[0.0002722036,0.0009202692,0.007495544,0.0002144901,0.0002022269,0.001132536,0.0007056427,0.7776775,0.08846066,0.009031102,0.1137769,0.00011084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08774193,0.0007751328,0.8844005,0.0007051801,0.0002362732,0.001579161,0.0002075581,0.004599815,0.01975437],"genre_scores_gemma":[0.4534235,0.0005981122,0.5320155,0.0001610969,0.00007818509,0.0008846087,0.0004189644,0.0001918286,0.01222823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002903143,"threshold_uncertainty_score":0.009711921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1556144380074251,"score_gpt":0.399868837379012,"score_spread":0.2442543993715869,"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."}}