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Record W2966822748 · doi:10.1109/icorr.2019.8779385

Load Carriage Device for Studying Medial-Lateral Stability of Walking: Design and Performance Evaluation

2019· article· en· W2966822748 on OpenAlexaff
Jean-Paul Martin, Qingguo Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsQueen's University
Fundersnot available
KeywordsBackpackTrunkOscillation (cell signaling)Computer scienceSpring (device)SimulationControl theory (sociology)AmplitudeStructural engineeringEngineeringPhysicsControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.214
GPT teacher head0.464
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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