Serum Fatty Acid Reference Ranges: Percentiles from a New Zealand National Nutrition Survey
Bibliographic record
Abstract
Serum fatty acids are increasingly used in cross-sectional surveys and cohort studies as biomarkers of dietary fat intake; however, it is currently difficult to judge whether an individual has low or high fatty acid status, or whether the distribution of fatty acids of a group of people is low or high due to a lack of appropriate reference values. In the absence of interpretive criteria, the distribution of serum fatty acids from a suitable reference population can be used as an alternative. We describe the distribution of the fatty acid composition of the three most commonly reported lipid classes in serum; cholesterol ester, phospholipid and triacylgycerol. Results for each serum lipid class are presented as means (SD) and percentiles (5, 10, 25, 50, 75, 90, and 95) of serum fatty acids in non-fasting blood samples collected from a population based cross-sectional survey of New Zealand adults (n = 2793). These serum fatty acid reference ranges are applicable and relevant to Australia, United Kingdom, and United States as well as other countries where fat intakes are similar to New Zealand.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".