Bibliographic record
Abstract
Incretin-based therapy promises to be a useful adjunct in the treatment of diabetes. Glucagon-like peptide-1 (GLP1) and, to a lesser extent, glucose-dependent insulinotropic polypeptide (GIP) are potent stimulators of insulin secretion, and consequently have significant effects on the regulation of the glucose metabolism. What has been less clear, however, is whether these hormones exert direct effects on glucose metabolism independent of their effect on pancreatic insulin and glucagon release. Glucose effectiveness and insulin action (the ability of glucose and insulin respectively to stimulate glucose uptake and suppress glucose release) have been reported by some investigators, but not others, to improve during incretin infusion. The purpose of this review is briefly to examine some of the numerous conflicting reports in the literature as to the presence or otherwise of extrapancreatic incretin effects. In addition, we will briefly discuss the gastrointestinal effects of incretins. These effects may be of considerable importance in the treatment of postprandial hyperglycemia although they are not, strictly speaking, the result of a direct incretin effect on glucose metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".