[Fat distribution and metabolism].
Bibliographic record
Abstract
It is well known that adipose tissue distribution is an important factor involved in the etiology of type 2 diabetes and cardiovascular diseases. Adipose tissue distribution is obviously different between men and women, men being prone to accumulate their excess of energy in the abdominal region, more specifically in the intra-abdominal depot (visceral) whereas women show a selective deposition of adipose tissue in the gluteo-femoral region. Several studies have demonstrated an association between age and adipose tissue distribution and a selective deposition of visceral adipose tissue has been reported with age, in both men and women. In this regard, the menopause transition also appears to be a factor associated with an accelerated accumulation of abdominal adipose tissue. This increase in visceral adipose tissue has been suggested to play a significant role in the etiology of metabolic complications increasing the risk of type 2 diabetes and cardiovascular diseases. However, a selective mobilization of visceral adipose tissue in response to a weight loss program has been noted among viscerally obese patients, this reduction in visceral adipose tissue being associated with improvements in the lipoprotein-lipid profile and insulin sensitivity. Thus, the distribution of adipose tissue is an important factor to take into account in the evaluation of the patient. Furthermore, the amount of abdominal adipose tissue should also be considered as an important therapeutic target for the optimal management of cardiovascular disease risk.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.021 |
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".