Change in heart rate variability during two firefighting work cycles
Bibliographic record
Abstract
This study aimed to determine whether the change in heart rate variability from pre to post firefighting is modulated by different work cycles. Thirteen male firefighters underwent two firefighting simulations that comprised two identical 25-min work bouts intercalated by a passive recovery period of either 20 min (T20) or 5 min (T5). The square root of the mean squared differences of successive R–R intervals (RMSSD) and aural temperature were measured at rest before (PRE) and after (POST) firefighting simulations. The decrease in RMSSD was different between firefighting simulations (T20: −10 ± 21.2 ms, T5: −19.9 ± 20.9 ms, interaction, p = 0.02). Post-firefighting aural temperature was greater (p = 0.05) in T5 (37.18 ± 0.53 °C) than in T20 (36.88 ± 0.49 °C). In conclusion, a shorter recovery period of 5 min between firefighting work bouts decreases post-firefighting heart rate variability, possibly attributed to a lower parasympathetic reactivation and a higher absolute value of body temperature.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".