Bibliographic record
Abstract
Obesity has become a global problem affecting adults and children alike. Lifestyle choices both personal and industry driven can be blamed for the rise in obesity. One must distinguish between the possibly reversible overweight condition and the almost intractable actual morbid obesity where predisposing genetic factors may come into play. Both however exhibit consequences to health with a severity that cannot be underestimated. Deleterious changes to metabolism can lead to type II diabetes and atherosclerosis and other organ dysfunctions. It has long been recognized that there are two main types of fatty tissue in the body, white adipose tissue (WAT) serving a storage function and brown adipose tissue (BAT) serving a thermogenic function. The new discovery has been that WAT cells can be induced to undergo conversion (browning) to BAT to yield what is called beige adipose tissue, acquiring the thermogenic function. The clinical dream is to be able to promote browning and to induce, what may be called, burning off the fat. In this B&B article I entice the reader with a recent study that shows how two key hormones insulin and leptin operate cooperatively in the brain to monitor and regulate energy balance and the downstream effect of browning. I present other studies to add additional perspectives to the understanding of the mechanisms in peripheral tissues and other hormones that play additional key roles. Whether obesity can be conquered therapeutically by manipulating the regulatory systems is still an open question.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.028 | 0.015 |
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".