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Record W4416827357 · doi:10.1002/cpz1.70228

Evoking Cutaneous Reflexes During Human Walking I. A Step‐by‐Step Methodological Approach

2025· article· en· W4416827357 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Protocols · 2025
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsReflexGaitTreadmillGait cycleFunctional electrical stimulationStimulation

Abstract

fetched live from OpenAlex

This paper, the first in a two-part series focused on measuring cutaneous reflexes during human walking, provides a detailed step-by-step methodology for reliably eliciting cutaneous reflexes during human treadmill walking. The procedure addresses the technical challenges of eliciting reflexes from cutaneous nerves in a consistent and reproducible manner throughout the gait cycle. Building on approaches used in previous studies, we integrate practical guidance on equipment setup, electrode placement, configuration of a foot-sensitive resistor for quantifying gait cycle parameters, and reflex measurements to enable successful implementation across laboratories with varying levels of expertise. The custom development and use of a pseudorandomized stimulation approach is a novel feature of our broader methodology and is described in detail in the second paper. The present protocol focuses on the experimental setup required to obtain high-quality reflex measurements during walking, thereby providing the basis for advanced stimulation paradigms in human sensorimotor research. © 2025 Wiley Periodicals LLC. Basic Protocol: Evoking cutaneous reflexes during human walking using a pseudorandomized approach.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.377
Teacher spread0.300 · 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