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Record W3174271247 · doi:10.1177/17479541211028578

Low glycemic CHO ingestion minimizes cognitive function decline during a simulated soccer match

2021· article· en· W3174271247 on OpenAlexaff
Manuel D. Quinones, Peter W.R. Lemon

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsWestern University
Fundersnot available
KeywordsIngestionPerceived exertionAnimal scienceGlycemicCognitionEndocrinologyMedicineInternal medicineChemistryDiabetes mellitusBiologyHeart rateBlood pressure

Abstract

fetched live from OpenAlex

Often cognitive function is affected adversely during prolonged, high intensity exercise. We assessed whether hydrothermally modified corn starch (HMS) ingestion minimizes cognitive decline with soccer play. 11 men (177.7 ± 6.8 cm, 77.3 ± 7.9 kg, 22 ± 3 y, 12.8 ± 4.9% body fat, [Formula: see text]O 2 max = 57.1 ± 3.9 ml•kg BM −1 •min −1 ; mean ± SD) completed 60 min simulated soccer matches with HMS (8% CHO; 0.7 g•kg BM −1 •h −1 ; 2.8 kcal·kg BM −1 •h −1 ) vs isoenergetic dextrose (DEX) consumed 30 min prior to the match and at half time. Compared to DEX, blood glucose was lower (p < 0.001) with HMS at 15 (5.3 ± 0.6 vs 7.7 ± 1.4 mmol•L −1 ) and 30 min post ingestion (5.6 ± 0.6 vs 8.3 ± 1.0 mmol•L −1 ), and greater (p = 0.004) after 15 min of play (5.8 ± 0.5 vs 5.1 ± 0.6 mmol•L −1 ). With HMS, perceived exertion ratings were reduced throughout the match (p = 0.025 at 15 min). Flanker test incongruent trial reaction time (p = 0.040) and conflict cost (p = 0.019) were both better with HMS. These data suggest that HMS ingestion minimizes cognitive decline during soccer play. More study is warranted to elucidate fully the cognition benefits of HMS ingestion for sport performance.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.272
Teacher spread0.264 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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