Meal Composition and Iron Status of Experienced Male and Female Distance Runners
Bibliographic record
Abstract
This study compared the iron status of middle-distance runners consuming meals providing low-medium iron availability (LMIA) or medium-high iron availability (MHIA), and determined the effect of a 4-week intervention on iron status in LMIA participants. Seventeen university-aged competitive runners and eight inactive controls participated. Mean serum ferritin levels were significantly greater in the MHIA group (58.7 ± 9.7ng·mL−1) than in the LMIA group (43.6 ± 10.9 ng·mL−1). Significant (p < 0.05) correlations were noted between absorbable dietary iron and serum iron (r = 0.639), total iron binding capacity (r = −0.636) and hemoglobin (r = 0.523). The mean absorbable dietary iron was significantly greater following the intervention in LMIA males (Test 1, 0.97 ± 0.3 mg·day−1; Test 2, 1.54 ± 0.5 mg·day−1; p < 0.05). Dietary advice did not improve iron status. These data suggest that meal composition may influence the amount of iron available for absorption and for maintaining iron status over time.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".