A suite of objective biomechanical measurement tools for personal load carriage system assessment
Why this work is in the frame
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Bibliographic record
Abstract
For application to military and civilian needs, Defence Research and Development Canada--Toronto contracted Queen's University, Kingston to develop a suite of biomechanical assessment and analytical tools to supplement human-based load carriage system assessment methods. This suite of tools permitted efficient objective evaluation of biomechanical aspects of load-bearing webbing, vests, packs and their components, and therefore contributed to early system assessment and a rapid iterative design process. This paper is a summary of five assessment and analytical tools. A dynamic load carriage simulator was developed to simulate cadence of walking, jogging and running. The simulator comprised a computer-controlled pneumatic platform that oscillated anthropometrically weighted mannequins of varying dimensions from which measures of skin contact pressure, hip reaction forces and moments and relative pack-person displacements were taken. A stiffness tester for range of motion provided force-displacement data on pack suspension systems. A biomechanical model was used to determine forces and moments on the shoulders and hips, and validated using a static load distribution mannequin. Subjective perceptual rating systems were used gather soldier feedback during a standardized mobility circuit. Objective outcome measures were validated by means of other objective measures (e.g., Optotrak, video, Instron, etc.) and then compared to subjective ratings. This approach led to development of objective performance criteria for load carriage systems and to improvements in load carriage designs that could be used both in the military and in general.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it