Urine specific gravity in exercisers prior to physical training
Bibliographic record
Abstract
Urine specific gravity (USG) is used as an index of hydration status. Many studies have used USG to estimate pre-exercise hydration in athletes. However, very little is known about the pre-exercise hydration status of recreational exercisers. The purpose of the present study was to measure the pre-exercise USG in a large sample of recreational exercisers who attended 2 different fitness centers in the United States. In addition, we wanted to determine if factors such as time of day, geographic location, and gender influenced USG. We tested 166 subjects in Chicago and 163 subjects in Los Angeles. Subjects completed a survey on their typical training regimen and fluid-replacement habits, and thereafter voided and delivered a urine sample to the investigators prior to beginning exercise. Samples were measured on site for USG using a hand-held refractometer. The mean (SD) USG was 1.018 (+/- 0.007) for all subjects. Males had a higher average USG (1.020 +/- 0.007) when compared with females (1.017 +/- 0.008; p = 0.001). Despite differences in climate, no difference in mean USG occurred based on location or time of day. Based on standards used for athletes (USG > or = 1.020), 46% of the exercisers were likely to be dehydrated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".