A Preliminary Investigation of the Effect of Protective Clothing Weight, Bulk and Stiffness on Combat Mobility Course Performance
Bibliographic record
Abstract
Soldier loads continue to rise in response to new technological capabilities and emerging threats. However, literature addressing the extent to which load mass properties affects operational task performance and mission outcome is sparse. The objective of this preliminary study was to quantify the effect of PPE mass properties (weight, bulk and stiffness) on combat mobility, as measured using the standardized Load Effects Assessment Program (LEAP) course. Twenty-four soldiers completed the LEAP course in three clothing and individual equipment (CIE) configurations (UE: unencumbered; FFO: full fighting order (FFO) without body armour; and FFO+: FFO with body armour). Significant differences between clothing conditions were revealed for LEAP performance metrics (overall course time). Regression analysis revealed significant relationships between overall mobility performance and condition mass properties of weight, bulk, and stiffness. Outcomes will influence the design of future CIE and future research in this area.
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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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".