Measurement of sodium concentration in sweat samples: comparison of 5 analytical techniques
Bibliographic record
Abstract
Sweat sodium concentration (SSC) can be determined using different analytical techniques (ATs), which may have implications for athletes and scientists. This study compared the SSC measured with 5 ATs: ion chromatography (IChr), flame photometry (FP), direct (DISE) and indirect (IISE) ion-selective electrode, and ion conductivity (IC). Seventy sweat samples collected from 14 athletes were analyzed with 5 instruments: the 883 Basic IC Plus (IChr, reference instrument), AAnalyst 200 (FP), Cobas 6000 (IISE), Sweat-Chek (IC), and B-722 Laqua Twin (DISE). Instruments showed excellent relative (intraclass correlation coefficient (ICC) ≥ 0.999) and absolute (coefficient of variation (CV) ≤ 2.6%) reliability. Relative validity was also excellent between ATs (ICC ≥ 0.961). In regards to the inter-AT absolute validity, compared with IChr, standard error of the estimates were similar among ATs (2.8-3.8 mmol/L), but CV was lowest with DISE (3.9%), intermediate with IISE (7.6%), and FP (6.9%) and highest with IC (12.3%). In conclusion, SSC varies depending on the AT used to analyze samples. Therefore, results obtained from different ATs are scarcely comparable and should not be used interchangeably. Nevertheless, taking into account the normal variability in SSC (∼±12%), the imprecision of the recommendations deriving from FP, IISE, IC, and DISE should have trivial health and physiological consequences under most exercise circumstances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".