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Record W1899321645 · doi:10.1186/1550-2783-12-s1-p53

Genetic variation related to caffeine metabolism or response during exercise

2015· article· en· W1899321645 on OpenAlexaff
Nanci S. Guest, Joseph Jamnik, Christopher J. Womack, Ahmed El‐Sohemy

Bibliographic record

VenueJournal of the International Society of Sports Nutrition · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineClinical nutritionCaffeineVariation (astronomy)Sports medicineMetabolismGenetic variationPhysiologyBioinformaticsInternal medicinePhysical therapyBiologyEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

Methods We examined whether a panel of 25 SNPs in 19 genes that might be related to caffeine metabolism or response modified exercise performance, or were associated with any physiologic outcomes during exercise. Subjects were trained male cyclists (n = 33) who underwent a doubleblind placebo-controlled crossover trial to test the effects of caffeine (6 mg/kg) on various performance parameters during a computer-simulated 40 km time trial. The 25 SNPs were genotyped using the Sequenom MassARRAY system, and caffeine-genotype interactions on time trial time, VO2 max, heart rate, respiratory exchange ratio and rate of perceived exertion were assessed using repeated measures analysis of variance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.286

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 head0.010
GPT teacher head0.245
Teacher spread0.236 · 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 designBench or experimental
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

Citations1
Published2015
Admission routes1
Has abstractyes

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