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Record W3134493031 · doi:10.1152/ajpendo.00574.2020

Higher protein intake during resistance training does not potentiate strength, but modulates gut microbiota, in middle-aged adults: a randomized control trial

2021· article· en· W3134493031 on OpenAlexaff
Colleen F. McKenna, Amadeo F. Salvador, Riley Hughes, Susannah E. Scaroni, Rafael A. Alamilla, Andrew T. Askow, Scott A. Paluska, A. C. Dilger, Hannah D. Holscher, Michael De Lisio, Naiman A. Khan, Nicholas A. Burd

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsResistance trainingGut floraMedicineRandomized controlled trialPhysiologyInternal medicineBiologyImmunology

Abstract

fetched live from OpenAlex

Our research evaluates the efficacy of higher in comparison with moderate animal-based protein intake on resistance exercise training-induced muscle strength, clinical biomarkers, and gut microbiota in middle-aged adults through a dietary counseling-controlled intervention. Higher protein intake did not potentiate training adaptations, nor did the intervention effect disease biomarkers. Both diet and exercise modified gut microbiota composition. Collectively, moderate amounts of high-quality, animal-based protein is sufficient to promote resistance exercise adaptations at the onset of aging.

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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 designRandomized trial
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

Citations34
Published2021
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Physiology-Endocrinology and MetabolismSame topicMuscle metabolism and nutritionFrench-language works237,207