Bibliographic record
Abstract
Postprandial lipemia (PPL) refers to a dynamic sequence of plasma lipid/lipoprotein changes induced by ingestion of food. PPL results from absorption of digested dietary lipids which form chylomicrons (CM) and increased hepatic production of VLDL, stimulated by increased delivery of fats to the liver. In general, PPL occurs over 4-6 h in normal individuals, depending on the amount and type of fats consumed. The complexity of PPL changes is compounded by ingestion of food before the previous meal is fully processed. PPL testing is done to determine the impact of (a) exogenous factors such as the amount and type of food consumed, and (b) endogenous factors such as the metabolic/genetic status of the subjects, on PPL. To study PPL appropriately, different methods are used to suit the study goal. This paper provides an overview of the methodological aspects of PPL testing. It deals with markers of postprandial lipoproteins, testing conditions and protocols and interpretation of postprandial data. The influence of the meal itself will not be discussed as it is the subject of another paper in this series.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".