Daily Controlled Consumption of an Electrokinetically Modified Water Alters the Fatigue Response as a Result of Strenuous Resistance Exercise
Bibliographic record
Abstract
Our objective was to assess the effects of consuming electrokinetically modified water (EMW) on fatigue attenuation and ratings of perceived exertion (RPE) following resistance exercise. A double-blind, placebo-controlled, two-arm trial was used in this investigation. Forty participants were randomly assigned to either an experimental or a placebo-control group. Participants consumed the EMW or placebo water daily for eighteen days prior to completing a fatigue protocol for the elbow flexors. The fatigue protocol consisted of a single bout of resistance exercise for the biceps brachii. Participants were tested for isometric strength before exercise and immediately following exercise. The maximal voluntary isometric contraction was used as the criterion measure for strength. To calculate the fatigue index, the postexercise maximal voluntary isometric contraction value was divided by the preexercise maximal voluntary isometric contraction value multiplied by 100. Also, ratings of perceived exertion (RPE) were assessed using the Borg scale. Fatigue indices and RPE were significantly lower for the experimental group compared to the control group ( P<0.05 ). Consuming EMW for eighteen days prior to high intensity resistance exercise can significantly enhance muscle contractile function by reducing muscle fatigue and RPE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".