A Case Study of the Short-Term Development of Body Composition and Substrate Utilization Following Prolonged Low-Intensity Ski Trekking with Inadequate Energy Intake in Svalbard
Bibliographic record
Abstract
This case study aimed to examine the short-term development of body composition and substrate utilization (i.e., contribution of fat and carbohydrates to energy supply) following prolonged low-intensity ski trekking (LIST) with inadequate energy intake in an Arctic region. For 23 days, two highly aerobically fit, male recreational athletes (24 and 26 years) performed ~2 – 11 hours of LIST each day, while pulling supply sledges (initially ~80 kg) across the length of Svalbard’s largest island, Spitsbergen (~640 km). We estimated body composition using bioelectrical impedance analysis (BIA). For evaluation of substrate utilization, we analyzed pulmonary respiratory gas-exchange ratio (RER) using an ergospirometry system during treadmill trekking (ski trekking simulation). Results indicated that the energy intake of each participant during this unsupported expedition was ~21.4 MJ·day-1 (~5107 kcal·day-1), of which ~33% (~5.0 g·kg-1·day-1), ~51% (~3.4 g·kg-1·day-1), and ~16% (~2.4 g·kg-1·day-1) came from carbohydrates, fat, and proteins, respectively. Body mass decreased by 7.2 kg (8.4%) in Subject A, and 4.4 kg (5.2%) in Subject B. Absolute fat mass decreased by 5.4 kg (37%) and 4.7 kg (30%) in Subject A and Subject B, respectively, whereas the changes in fat-free mass (–1.8 kg in Subject A, and +0.3 kg in Subject B) were within the random measurement error of the BIA analyser. Changes in RER in Subject A (–0.01 to –0.02 units) were within the random measurement error, whereas the RER data in Subject B were not interpretable due to excessive fluctuations in ventilatory equivalent for oxygen. In conclusion, this study indicates that short-term, prolonged LIST, performed with an energy deficit corresponding to a weight loss of ~2 kg·week-1, can lead to leaner body composition without notable changes in fat-free mass in well-trained, male recreational athletes. Furthermore, substrate utilization does not appear to be affected by short-term, prolonged LIST in this subgroup of athletes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".