An Evaluation of Omega-3 Status and Intake in Canadian Elite Rugby 7s Players
Bibliographic record
Abstract
BACKGROUND: EPA and DHA n-3 FA play crucial roles in both neurological and cardiovascular health and high dietary intakes along with supplementation suggest potential neuroprotection and concussion recovery support. Rugby athletes have a high risk of repetitive sub-concussive head impacts which may lead to long-term neurological deficits, but there is a lack of research looking into n-3 FA status in rugby players. We examined the dietary n-3 FA intake through a FFQ and n-3 FA status by measuring the percentage of n-3 FA and O3I in elite Canadian Rugby 7s players to show distribution across O3I risk zones; high risk, <4%; intermediate risk, 4 to 8%; and low risk, >8%. METHODS: = 15; 23.45 ± 3.10 years; 71.21 ± 5.79 kg) athletes. RESULTS: = 0.183), with a greater proportion of non-supplemented athletes in the high-risk category (45.5% vs. 39.1%). Dietary intake in non-supplemented athletes did not meet daily dietary recommendations for ALA or EPA + DHA compared to supplemented athletes. CONCLUSIONS: Overall, despite supplementation, O3I score remained in the high-risk category in a proportion of athletes who met recommended n-3 FA dietary intakes, and non-supplemented athletes had a higher proportion of O3I scores in the high-risk category, suggesting that dietary intake alone may not be enough and athletes may require additional dietary and n-3 FA supplementation to reduce neurological and cardiovascular risk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".