Modeling glucose control on endogenous glucose production in nonsteady state: necessity of direct and delayed signalling
Bibliographic record
Abstract
So far the modalities of glucose control on endogenous glucose production (EGP) under dynamic conditions have been poorly investigated. In the present study we developed models to describe glucose control on EGP under nonsteady-state conditions. The database consisted of experiments during which insulin was maintained at the basal level, glucose concentration exhibited a meal-like profile, and a glucose tracer was infused in such a way to clamp tracer glucose specific activity. This optimal protocol allowed us: (1) to rule out the possibly confounding effect of hyperinsulinemia on the assessment of glucose control on EGP, and (2) to ensure an accurate assessment of the time course of EGP during the nonsteady state. Three models of increasing complexity were formulated, employing different combinations of two modalities of glucose control on EGP, one exerted by glucose in plasma and the other one by glucose in a remote glucose compartment. Each model providing indices measuring glucose inhibitory action on EGP (glucose effectiveness) and the delay of glucose action on EGP. The best model is the one which embodies both direct and delayed glucose control on EGP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".