Assessment of linoleic acid, linolenic acid, arachidonic acid, and docosahexaenoic acid intakes in 4–7 year old healthy children
Bibliographic record
Abstract
Retinal and neuronal growth continues throughout childhood, therefore it is conceivable that low intake of AA and DHA may have an impact on development. The objective was to study the diets of children to determine the current intakes of linoleic acid (LA), linolenic acid (ALA), arachidonic acid (AA) and docosahexaenoic acid (DHA). Healthy children (n=91), 4–7 years of age, living in central Alberta, Canada agreed to participate in this cross‐sectional study. Parents were instructed to document all food and drink consumed by their child for 3 consecutive days. Seventy‐eight children completed the study. In 64 of 78 subjects LA intake was lower (7.4±3.3 g/day) compared to the adequate intake for LA (10 g/day) for those children 4–8 years of age. In 56 of the 78 subjects, ALA intake was also lower (0.71±0.5 g/day) compared to the adequate intake for ALA (0.9 g/day) for children 4–8 years of age. AA and DHA intakes were 57±35 mg/day and 37±63 mg/day, ranged between 0–350 mg/day and 1.2–180 mg/day and varied day to day at 0–991 mg/d and 0–380 mg/day, respectively. On a body weight basis this intake level is approximately 6.3% and 7.7% of the level of AA and DHA intake at the time of weaning from human milk or infant formula containing long chain polyunsaturated fatty acids. It is concluded that Canadian children, 4–7 years of age and not living near a marine environment, have relatively low intakes of AA and DHA. This work was financially supported by the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".