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Record W2046487481 · doi:10.1111/nure.12124

Performance effects and metabolic consequences of caffeine and caffeinated energy drink consumption on glucose disposal

2014· review· en· W2046487481 on OpenAlex
Jane Shearer, Terry E. Graham

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNutrition Reviews · 2014
Typereview
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsUniversity of GuelphUniversity of Calgary
Fundersnot available
KeywordsCaffeineInsulin resistanceMedicineInternal medicineEndocrinologyInsulinPhysiology

Abstract

fetched live from OpenAlex

This review documents two opposing effects of caffeine and caffeine-containing energy drinks, i.e., their positive effects on athletic performance and their negative impacts on glucose tolerance in the sedentary state. Analysis of studies examining caffeine administration prior to performance-based exercise showed caffeine improved completion time by 3.6%. Similar analyses following consumption of caffeine-containing energy drinks yielded positive, but more varied, benefits, which were likely due to the diverse nature of the studies performed, the highly variable composition of the beverages consumed, and the range of caffeine doses administered. Conversely, analyses of studies administering caffeine prior to either an oral glucose tolerance test or insulin clamp showed a decline in whole-body glucose disposal of ~30%. The consequences of this resistance are unknown, but there may be implications for the development of a number of chronic diseases. Both caffeine-induced performance enhancement and insulin resistance converge with the primary actions of caffeine on skeletal muscle.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.055
GPT teacher head0.367
Teacher spread0.312 · 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