Autonomic and cortical response of soldiers in different combat scenarios
Bibliographic record
Abstract
INTRODUCTION: The study of chronic and acute responses when exposed to extreme, aggressive and stressful environments, such as in combat environments, is becoming increasingly popular as such information leads to better optimisation of soldiers' physical and psychological performance, as well as mission effectiveness and efficiency. Due to internal complexity, uncertainty and variability of real combat scenarios, a specific approach to all possible types of military combat scenarios is necessary. METHODS: Modifications in the autonomic modulation and cortical arousal before and after asymmetrical, symmetrical and close quarter combat simulations were analysed in 31 male professional veteran soldiers (age: 34.5±4.2 years) with between seven and 18 years of experience in their respective units, as well as experience in international missions in current conflict areas such as Lebanon, Afghanistan, Bosnia, Kosovo and Iraq. RESULTS: The three combat situations produced a non-significant decrease in cortical arousal after combat simulations, presenting a trivial effect size in symmetrical and close quarter combat situations and a small effect size in asymmetrical situations. HR increased significantly in the three combat situations, and close quarter combat produced the highest sympathetic modulation of the three situations analysed. CONCLUSION: Symmetrical, asymmetrical and close quarter combat situations produced an increase in sympathetic modulation, being highest in the close quarter combat situation, where actions are performed at a close distance and in closed spaces.
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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) | 0.002 | 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".