Gestational age and birth weight in relation to n−3 fatty acids among inuit (Canada)
Bibliographic record
Abstract
Seafood consumption during pregnancy carries both benefits (high n-3 FA intake) and risks (exposure to environmental contaminants) for the developing fetus. We determined the impacts of marine n-3 FA and environmental contaminants on gestational age (GA) of Nunavik women and the anthropometric characteristics of their newborns. FA and contaminant (polychlorinated biphenyls and mercury) concentrations were measured in cord plasma of Nunavik newborns (n = 454) and compared with those of a group of newborns (n = 29) from southern Québec. Data were collected from hospital records and birth certificates. In Nunavik newborns, arachidonic acid (AA) was two times lower (P < 0.0001), whereas DHA concentration, the sigman-3 / sigman-6 ratio, and the percentage of n-3 highly unsaturated FA (HUFA) (of the total HUFA) were three times higher (P < 0.0001) compared with southern Québec newborns. After controlling for confounders, GA and birth weight were higher by 5.4 d [95% confidence interval (CI): 0.7-10.1] and 77 g (95% CI: -64 to 217) in the third tertile of percentage of n-3 HUFA (of the total HUFA) as compared with the first tertile. There was no evidence that contaminants had negative effects on GA or birth weight. In this seafood-eating population, an increase in the proportion of n-3 HUFA (of the total HUFA), measured in umbilical cord plasma phospholipids, was associated with a significantly longer GA.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".