ENERGY EXPENDITURE AND BODY COMPOSITION RESPONSES TO THE FIRST UNSUPPORTED SKI-TREK ACROSS THE ARCTIC OCEAN
Bibliographic record
Abstract
Two experienced polar explorers (RG, TL) completed the first unsupported ski crossing of the Arctic icecap (Arctic Ocean 2000 Expedition) from Siberia to the North Pole and on to Cape Discovery, Canada in 109 days, covering 1914 km. The trekkers used sleds and rucksacks to transport their loads (200 kg each at the start of the expedition). On a previous 86 day, 2928 km, Greenland expedition these trekkers maintained their fat-free mass (FFM) in spite of large fat mass (FM) losses due to high energy expenditures. The purpose of this study was to see if this preservation of FFM would occur under conditions of much higher daily energy expenditure (DEE) for a longer period of time. The trekkers ate a diet with 63.5% MJ from fat, 28.5% MJ from carbohydrate, 8% MJ from protein, with a mean daily energy intake (DEI) of 21.5 MJ for TL and 22.1 MJ for RG. DEXA was used to assess body composition changes pre- and post-expedition. The energy cost of transporting them and their supplies resulted in large losses of FM (RG = −12.7 kg, TL = −22.5 kg) with minor losses of FFM (RG = −1.0 kg, TL = −1.5 kg). Conservative energy expenditure calculations based on DEI and changes in FM and FFM shows the mean DEE over the entire expedition was 29.7 MJ for TL and 26.7 MJ for RG. These DEEs are among the highest reported and are comparable to those reported by Stroud et al. (1997) during a trans-Antarctic trek: also they exceed the mean DEEs reported for Tour de France cyclists by 8–9% (Saris, et al., 1986). The large body sizes of the trekkers in combination with their long days of extreme physical activity account for their high DEEs. Their combination of high exercise work loads and high caloric throughout may be responsible for the preservation of FFM in the face of such large losses of FM.Table: Body Composition Changes
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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 | 0.001 |
| 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".