{"id":"W3211922492","doi":"10.1371/journal.pdig.0000072","title":"A parsimonious model of blood glucose homeostasis","year":2022,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Mitacs; University of Ontario Institute of Technology","keywords":"Glucose homeostasis; Data assimilation; Computer science; Homeostasis; Diabetes mellitus; Biological system; Applied mathematics; Mathematics; Biology; Physics; Endocrinology; Insulin resistance","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001139428,0.00012122,0.0002252959,0.00005951112,0.0001307781,0.0000138107,0.0002100195,0.00003487948,0.00001578985],"category_scores_gemma":[0.00001680786,0.0001328641,0.000143465,0.0001898887,0.00004162766,0.000003891853,0.0002660404,0.00007740155,0.000002480854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002853518,"about_ca_system_score_gemma":0.0002801436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001211454,"about_ca_topic_score_gemma":0.00001134101,"domain_scores_codex":[0.9988243,0.00004624727,0.0002828637,0.0002980127,0.0002603612,0.0002882144],"domain_scores_gemma":[0.9992468,0.00000682668,0.0001614353,0.0004059579,0.00004433633,0.0001346278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001082079,0.01279302,0.02866998,0.001125462,0.004910537,0.00003805635,0.001500479,0.4500652,0.2960943,0.0009717633,0.03698022,0.1657689],"study_design_scores_gemma":[0.008870487,0.01481186,0.001680823,0.000124063,0.001143013,0.0002119221,0.002744985,0.1658407,0.7400924,0.005423116,0.05551225,0.003544386],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917828,0.006892438,0.0002093189,0.0002144342,0.00002255036,0.0001502349,0.0003249741,0.00001520162,0.0003879977],"genre_scores_gemma":[0.9984755,0.0003282067,0.0002359079,0.0003044553,0.00004203085,0.00002998561,0.0002847788,0.00002634756,0.0002727991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4439981,"threshold_uncertainty_score":0.5418038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689625262212086,"score_gpt":0.2373291821398534,"score_spread":0.2204329295177325,"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."}}