Bibliographic record
Abstract
The metabolic syndrome represents a vicious cycle whereby insulin resistance leads to compensatory hyperinsulinaemia, which maintains normal plasma glucose but may exacerbate insulin resistance. Excess insulin secretion may eventually reduce beta-cell function due to amyloid deposition, leading to raised blood glucose and further deterioration of beta-cell function and insulin sensitivity via glucose toxicity. Reducing postprandial glucose and insulin responses may be a way to interrupt this process, but there is disagreement about the dietary approach to achieve this. Glucose and insulin responses are determined primarily by the amount of carbohydrate consumed and its rate of absorption. Slowly absorbed, low glycaemic-index (GI) foods are associated with increased HDL cholesterol and reduced risk of type 2 diabetes. There is some evidence that low-GI foods improve insulin sensitivity in humans, although studies using established techniques (glucose clamp or frequently sampled intravenous glucose tolerance test) have not been done. Low carbohydrate diets have been suggested to be beneficial in the treatment of the metabolic syndrome because of reduced postprandial insulin. However, they may increase fasting glucose and impair oral glucose tolerance--effects which define carbohydrate intolerance. The effects of low carbohydrate diets on insulin sensitivity depend on what is used to replace the dietary carbohydrate, and the nature of the subjects studied. Dietary carbohydrates may affect insulin action, at least in part, via alterations in plasma free fatty acids. In normal subjects a high-carbohydrate/low-GI breakfast meal reduced free fatty acids by reducing the undershoot of plasma glucose, whereas low-carbohydrate breakfasts increased postprandial free fatty acids. It is unknown if these effects occur in insulin-resistant or diabetic subjects. Thus further work needs to be done before a firm conclusion can be drawn as to the optimal amount and type of dietary carbohydrate for the treatment of the metabolic syndrome.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".