Bibliographic record
Abstract
Objective: To quantify the impact of eastward long haul travel on diurnal variations in cortisol, psychological sensations and daily measurements of physical performance. Methods: Five elite Australian skeleton athletes undertook a long haul eastward flight from Australia to Canada (LHtravel), while seven elite Canadian skeleton athletes did not travel (NOtravel). Salivary cortisol was measured on awakening, 60 min and 120 min after awakening. Psychological sensations were measured with a questionnaire, and maximal 30 m sprints were performed once a day between 09:30 and 11:00 h local time. Results: Compared with baseline, average (SD) resting salivary cortisol decreased by 67 % immediately after long haul travel (23.43 (5.71) nMol/l) (mean¡90 % confidence interval) in the LHtravel group (p = 0.03), while no changes were found in the NOtravel group (p = 0.74). There were no significant differences in 30 m sprint time between baseline and post-flight tests in the LHtravel group (p.0.05). The LHtravel group perceived themselves as ‘‘jet lagged’ ’ for up to 2 days after the flight (p = 0.01 for both midday lunch and evening dinner). Conclusions: Despite a distinct phase change in salivary cortisol rhythmicity and the athletes perceiving themselves as ‘‘jet lagged’’, minimal disturbances in ‘‘one-off’ ’ maximal sprinting ability between 09:30 and 11:00 h local time were seen in a group of elite skeleton athletes after long haul eastward travel from Australia to Canada. E lite athletes tend to undertake multiple extensive flights to
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.830 | 0.695 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".