MétaCan
Menu
Back to cohort
Record W2886707287 · doi:10.14198/jhse.2018.134.10

Is sodium a good hyperhydration strategy in 10k runners?

2018· article· en· W2886707287 on OpenAlex

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

VenueJournal of Human Sport and Exercise · 2018
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDehydrationChemistrySodiumUrine specific gravityAnimal scienceUrineIngestionBlood pressureInternal medicineEndocrinologyBiochemistryMedicineBiology

Abstract

fetched live from OpenAlex

The objective of the present study was to evaluate the effect of pre-exercise hyperhydration with sodium (PEHS), on the state of hydration and performance in runners of a 10K. Ten male runners (age 40.5 9.7 yrs, weight 72.5 8.4 kg, body fat 18.8 4.5%) participated in the study and performed 10 km of street running under two different forms of prehydration: pre-exercise hydration (PEH), consisting of water intake ad libitum, and pre-exercise sodium hyperhydration (PEHS), consisting of sodium ingestion (12 mg of sodium for each 5 mL of water) diluted 1 h before the test. The variables evaluated were heart rate (HR), body temperature (BT), body mass (BM), blood pressure (BP), relative dehydration (RD), absolute dehydration (AD), total ingested water (TH2OING), degree of dehydration (DD), sweating rate (SR), specific gravity of urine

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.034
GPT teacher head0.319
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