Heart Rate Variability in an Elite Female Alpine Skier: a Case Study
Bibliographic record
Abstract
Objectives. The purpose of this study was to assess the heart rate variability (HRV) during off-snow and on-snow training in an elite female alpine ski racer. Methods. Using a case study design, a single elite female alpine ski racer (25 years old; 175.6 cm; 69.9 kg) was recruited from the Canadian Alpine Ski Team. Training load was obtained using the sessional rating of perceived exertion method (sRPE), and a weekly sum was calculated using all training loads in a calendar week. Resting heart rate was recorded upon waking using a heart rate monitor. HRV was calculated using the natural logarithms of the root mean square of the successive differences of R-R intervals (lnRMSSD), and the coefficient of variation of lnRMSSD (lnRMSSDCV) with smallest worthwhile change (SWC). Compliance was 19.53%. Results. An inverse relationship was identified between the extreme values for lnRMSSD and sRPE. Daily lnRMSSDCV found two time-points that were significantly greater than SWC. The regression analysis of daily lnRMSSDCV over time had a positive slope of 0.001 (R = 0.0029). Three major depressions in lnRMSSD were observed over the recording period and two coincided with peak sRPE. The largest depression occurred on the same day the subject sustained a shoulder dislocation during a routine strength training session. The subject maintained training status over the training period but it was not predictive of future performance.
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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 | 0.005 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".