Progressive Heat Storage during Intermittent Work
Bibliographic record
Abstract
Ten participants (5M, 5F) completed 3 × 30‐min bouts of exercise (Ex 1, 2, 3) at a metabolic heat load (M‐W) of 505±7 W separated by 3 × 15‐min recovery (Rec 1, 2, 3) in an air calorimeter at 30°C, 30% RH. Rates of evaporative heat loss (EHL), dry heat loss (DHL) and M‐W were measured throughout by whole‐body direct calorimetry, giving changes in body heat content (ΔH b ). Rectal (T re ), quadriceps (T quad ) and triceps (T tri ) temperature were measured throughout. ΔH b progressively increased from the end of Ex 1 (242±18 kJ) to end Ex 2 (308±29 kJ), to end Ex 3 (341±46 kJ). Heat content dissipated during Rec 1 (−63±10 kJ) was similar to Rec 2 (−74±9 kJ) and Rec 3 (−73±7 kJ). T re progressively increased from 36.88±0.11°C at rest to 37.41±0.12°C at the end of Ex 1, 37.64±0.12°C (Ex 2), and 37.74±0.12°C (Ex 3). T tri increased from 33.91±0.19°C at rest, to 34.86±0.25°C (Ex 1), 35.23±0.28°C (Ex 2), and 35.40±0.33°C (Ex 3). However, after an initial increase in T quad from 34.62±0.14°C at rest to 36.82±0.16°C (Ex 1), no further significant elevations were observed. DHL was between ~50 and 65 W throughout. At the end of Ex 1 (383±25 W), Ex 2 (398±9 W) and Ex 3 (413±9 W) EHL was similar; however EHL increased at a greater rate during Ex 2 and 3 relative to Ex 1. Progressive elevations in body heat content, core temperature and inactive muscle temperature occurred with intermittent exercise. Supported by NSERC and US Army Medical Research Grant.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".