Load Carriage Device for Studying Medial-Lateral Stability of Walking: Design and Performance Evaluation
Bibliographic record
Abstract
When walking, the trunk not only oscillates in the vertical direction, but also in the medial-lateral direction. We developed a novel backpack that uses the medial-lateral oscillations of the trunk as input motion to drive medial-lateral oscillations of weight carried in a modified backpack. We use a combination of spring and damping elements to control mass motion, resulting in the ability to prescribe a variety of mass oscillation amplitudes and phase angles. We propose the device as a platform that can be used to study medial-lateral stability during walking. In particular, if the body's ability to predict medial-lateral centre-of-mass state is affected by an oscillating external mass. In this paper, we present the design, model, and model evaluation of our novel load carriage device. During testing, our model was able to predict the oscillation dynamics of the carried mass while walking: demonstrating its capability to create a variety of load carriage scenarios for the user.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".