Bibliographic record
Abstract
It has been known for more than 30 years that growth hormone has a lipolytic properties and growth hormone excess (acromegaly) and growth hormone deficiency have been reported to be associated with abnormalities in serum lipoprotein concentrations. Due to the lipolytic effect of growth hormone, its administration in man has been reported to increase plasma nonesterified fatty acid (NEFA) concentrations. Ketone body production increases during acute growth hormone excess as a result of increased NEFA concentrations; similarly, the increase in serum triglycerides may be explained by an increase in substrate (NEFA) supply to the liver for VLDL production. The effect may be enhanced by a simultaneous decrease of serum lipoprotein lipase activity. The cholesterol-lowering effect of growth hormone administration has not been investigated in detail, specifically, the effect of growth hormone on LDL kinetics is unknown. Growth hormone-excess and growth hormone deficiency have been reported to be associated with increased risk for atherosclerosis; an association with serum lipoprotein changes is likely but evidence for a causal link is yet lacking.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.006 | 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".