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Record W2048628789 · doi:10.1055/s-0030-1251992

Energy Expenditure in the Race Across America (RAAM)

2010· article· en· W2048628789 on OpenAlexaff
Andrew T. Hulton, Ian M. Lahart, Kristen L. Williams, Richard Godfrey, Sarah Charlesworth, Mathew G Wilson, Charles R. Pedlar, Greg Whyte

Bibliographic record

VenueInternational Journal of Sports Medicine · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnergy expenditureEnergy balanceAnimal scienceDoubly labeled waterTotal energy expenditureBalance (ability)Total energyBody weightMedicineMathematicsInternal medicineBiologyPhysical therapyPsychologyEcology

Abstract

fetched live from OpenAlex

Energy Expenditure was measured with doubly labelled water technique during heavy sustained exercise with an official finishing team in the Race Across America. Energy Intake was also calculated to produce an energy balance for the race. A team of 4 cyclists (Mean +/-SD age: 37+4 yr; body height: 182+8 cm; body mass: 80.8+6.6 kg) completed the race in a relay fashion. The team completed the race in 6 days 10 h and 51 min. Total mean energy expenditure was found to be 43,401 kcals (181,711 kJ) with a mean daily energy expenditure of 6,420 kcals (26,879 kJ). Total mean energy intake from all food and drink consumed was calculated at 29,506 kcals (123,536 kJ) with a mean daily energy intake of 4 918 kcals (20,591 kJ). This resulted in a total mean energy deficit of 13,878 kcals (58,104 kJ) with a mean daily energy deficit of 1,503 kcals (6,293 kJ). The high energy expenditure highlights the need for correct and practical dietary strategies and challenges nutritionists to devise high energy diets that not only contain the correct macronutrient balance, but are also palatable to the cyclists, thus encouraging a high energy intake.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.287
Teacher spread0.281 · 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 designNot applicable
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

Citations42
Published2010
Admission routes1
Has abstractyes

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