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The effects of magnesium supplementation on exercise performance

2001· article· en· W2002148770 on OpenAlexaff
E Finstad, Ian Newhouse, Henry C. Lukaski, Jim McAuliffe

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2001
Typearticle
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsLakehead University
Fundersnot available
KeywordsAnaerobic exerciseCrossover studyPlaceboHematocritMedicineVO2 maxMagnesiumTreadmillHeart rateHemoglobinPhysical therapyAnimal scienceBlood pressureInternal medicineChemistry

Abstract

fetched live from OpenAlex

PURPOSE: To determine the effects of magnesium (Mg2+) supplementation on performance and recovery in physically active women using the sensitive and recently advanced measure of ionic Mg2+ (iMg). METHODS: Participants (N = 121) were screened for [iMg] in plasma, with 44 (36.4%) exhibiting [iMg] below the normal range of 0.53-0.67 mmol.L-1 (4). Thirty-two subjects (21 +/- 3 yr) representing a broad range of [iMg] (0.54 +/- 0.04 mmol.L-1) completed the main 14-wk study. At baseline, participants submitted to a resting blood pressure measurement, and they completed both an anaerobic treadmill test and an incremental (aerobic) treadmill test. For the latter, values for workload, oxygen uptake, and heart rate were obtained at both anaerobic threshold and maximal effort. Blood samples for iMg, total serum Mg2+ (TMg), erythrocyte Mg2+ (EMg), Ca2+, K+, Na+, hemoglobin, hematocrit, lactate, and glucose were also collected pretest, and 4, 10, 30 min, and 24 h posttest. Subjects received 212 mg.d-1 Mg oxide or placebo in a double-blind fashion and were retested after 4 wk. After a 6-wk washout period, the testing was repeated with a treatment crossover. RESULTS: Ionic Mg2+ increased with Mg2+ treatment versus placebo (P < 0.05); however, performance and recovery indices were not significantly affected. CONCLUSION: Four weeks of 212 mg.d-1 Mg oxide supplementation improves resting [iMg] levels but not performance or recovery in physically active 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 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.294
Teacher spread0.284 · 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 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

Citations51
Published2001
Admission routes1
Has abstractyes

Explore more

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