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Record W2119869756 · doi:10.1136/bjsm.2006.033233

Effect of long haul travel on maximal sprint performance and diurnal variations in elite skeleton athletes

2007· article· en· W2119869756 on OpenAlexaboutno aff
Nicola Bullock, David T. Martin, Angus Ross, Doug Rosemond, Frank E. Marino

Bibliographic record

VenueBritish Journal of Sports Medicine · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsnot available
Fundersnot available
KeywordsSprintAthletesEveningElite athletesMedicinePhysical therapyPsychologyDemographyPhysics

Abstract

fetched live from OpenAlex

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 (LH(travel)), while seven elite Canadian skeleton athletes did not travel (NO(travel)). 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 LH(travel) group (p = 0.03), while no changes were found in the NO(travel) group (p = 0.74). There were no significant differences in 30 m sprint time between baseline and post-flight tests in the LH(travel) group (p>0.05). The LH(travel) 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.237
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2007
Admission routes1
Has abstractyes

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