Energy expenditure of international female rugby union players during a major international tournament: a doubly labelled water study
Bibliographic record
Abstract
The purpose of this study was to quantify the total energy expenditure (TEE) of international female rugby union players. Fifteen players were assessed over 14 days throughout an international multi-game tournament, which represented two consecutive one-match microcycles. Resting metabolic rate (RMR) and TEE were assessed by indirect calorimetry and doubly labelled water, respectively. Physical activity level (PAL) was estimated (TEE:RMR). Mean RMR, TEE, and PAL were 6.60 ± 0.93 MJ·day −1 (1578 ± 223 kcal·day −1 ), 13.51 ± 2.28 MJ·day −1 (3229 ± 545 kcal·day −1 ), and 2.0 ± 0.3 AU, respectively. There was no difference in TEE (13.74 ± 2.31 (3284 ± 554 kcal·day −1 ) vs. 13.92 ± 2.10 MJ·day −1 (3327 ± 502 kcal·day −1 ); p = 0.754), or PAL (2.06 ± 0.26 AU vs. 2.09 ± 0.23 AU; p = 0.735) across microcycles, despite substantial decreases in training load (total distance: −8088 m, collisions: −20 n, training duration: −252 min). After correcting for body composition, there was no difference in TEE (13.80 ± 1.74 (3298 ± 416 adj. kcal·day −1) vs. 13.16 ± 1.97 (3145 ± 471 adj. kcal·day −1 ) adj. MJ·day −1 , p = 0.190), RMR (6.49 ± 0.81 (1551 ± 194 adj. kcal·day −1 ) vs. 6.73 ± 0.83 (1609 ± 198 adj. kcal·day −1 ) adj. MJ·day −1 , p = 0.633) or PAL (2.15 ± 0.14 vs. 1.87 ± 0.26 AU, p = 0.090) between forwards and backs. For an injured participant ( n = 1), TEE reduced by 1.7 MJ·day −1 (−401 kcal·day −1 ) from pre-injury. For participants with illness ( n = 3), TEE was similar to pre-illness (+0.49 MJ·day −1 (+117 kcal·day −1 )). The energy requirements of international female rugby players were consistent across one-match microcycles. Forwards and backs had similar adjusted energy requirements. These findings are critical to inform the dietary guidance provided to female rugby players.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".