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CREATINE-LOADED BODY MASS INCREASES ARE NOT EXPLAINED BY WATER CHANGES ASSESSED BY MULTIFREQUENCY BIOIMPEDANCE ANALYSIS

2003· article· en· W2093717433 on OpenAlexaff
Julianna Berardi, Eric E. Noreen, Peter W.R. Lemon

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2003
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsBody waterAnimal scienceCreatineChemistryBody mass indexBody weightMedicineInternal medicineBiology

Abstract

fetched live from OpenAlex

It is known that 5d of creatine (Cr)-loading leads to increases in body mass. Some have speculated that this increase in mass is due to an increase in total body water (TBW), primarily intracellular fluid (ICF). PURPOSE To determine whether changes in mass due to Cr-loading can be explained by changes in body water as estimated by multifrequency bioelectric impedance analysis (MBIA). METHODS 37 men between the ages of 18 and 28 y completed 5d of Cr-loading (270 mg·kg−1·d−1). Before and after loading, body mass was measured using a calibrated weigh scale and body water was estimated according to NIH guidelines (1994) using the Xitron 4200 MBIA. RESULTS Cr-loading resulted in an increase in mass (+0.56±0.21kg, P< 0.001, mean±SEM). TBW also increased (+1.12±0.24L, P< 0.001) with Cr-loading, as did ICF (+0.97±0.22L, P< 0.05); however, the estimate of TBW was 100% greater than the observed increase in mass (P= 0.08). In addition, the correlations found for changes in TBW and mass (r= 0.092, P= 0.595, r2= 0.008) or ICF and mass (r= 0.011, P= 0.951, r2= 0.0001) were nonsignificant. CONCLUSION Body water changes assessed by MBIA do not accurately reflect the observed changes in body mass with Cr-loading. Supported by the Joe Weider Foundation

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.291
Teacher spread0.270 · 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.

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

Citations0
Published2003
Admission routes1
Has abstractyes

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