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Effects of exercise and thermal stress on caffeine pharmacokinetics in men and eumenorrheic women

2002· article· en· W2000888136 on OpenAlexaff
C. McLean, Terry E. Graham

Bibliographic record

VenueJournal of Applied Physiology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCaffeinePharmacokineticsHeat stressMedicineExercise physiologyInternal medicinePhysical exerciseEndocrinologyAnimal scienceBiology

Abstract

fetched live from OpenAlex

The influence of gender, exercise, and thermal stress on caffeine pharmacokinetics is unclear. We hypothesized that these factors would not have an effect on the metabolism of caffeine. Eight women participated in four 8-h trials and six men participated in two 8-h trials after the ingestion of 6 mg/kg caffeine. The women performed two resting trials (1 in the follicular phase and 1 in the luteal phase of the menstrual cycle) and two exercise trials (90 min of cycling exercise at 65% of maximal O(2) uptake, 1 h after caffeine ingestion) in the follicular phase (1 without and 1 with an additional thermal stress). The men performed one exercise and one resting trial. Menstrual cycle, gender, and exercise, with or without an additional thermal stress, had no effect on the pharmacokinetic measurements or urine caffeine. There was a trend for higher plasma caffeine and lower plasma paraxanthine concentrations in the women. These results confirm that gender, exercise, and thermal stress have no effect on caffeine pharmacokinetics in men and women.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.207
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations91
Published2002
Admission routes1
Has abstractyes

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