Intestinal temperature does not reflect rectal temperature during prolonged, intense running with cold fluid ingestion
Bibliographic record
Abstract
It is generally assumed that intestinal temperature (Tint), as measured with a telemetric pill, agrees relatively well with rectal temperature (Trec) during exercise. However, whether Tint reflects Trec during prolonged, intense and continuous exercise when cold fluids are consumed is unknown. Therefore, we compared Trec and Tint during a half-marathon during which cold water was ingested to prevent bodyweight (BW) losses >2%. Nine endurance athletes (age 30 ± 5 years) underwent a 21.1 km running time-trial (TT) in the heat (~30 °C and 44% RH) while BW losses were maintained to ~1% with continuous cold (4 °C) water provision. Tint and Trec were monitored throughout the TT. Hypohydration level, TT time and fluid intake were 1.2 ± 0.4% BW, 93.2 ± 9.9 min and 2143 ± 264 ml, respectively. Trec was systematically higher than Tint by 0.25 °C (95% CI: 0.14-0.37 °C). Tint and Trec showed an excellent relative (r = 0.90, p < 0.01), but poor absolute agreement as reflected by a 95% limit of agreement of ±1.07 °C and a standard error of measurement of ±0.39 °C. In conclusion, Tint does not mirror Trec during prolonged, intense running with cold fluid ingestion and, therefore, these measures should not be used interchangeably under this scenario.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".