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Record W3168626569 · doi:10.1123/mc.2020-0106

State and Trait Fatigue and Energy Predictors of Postural Control and Gait

2021· article· en· W3168626569 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

VenueMotor Control · 2021
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysical medicine and rehabilitationGaitTraitPsychologyPhysical therapyMedicineComputer science

Abstract

fetched live from OpenAlex

Compromised attentional resources during perceived fatigue has been suggested to alter motor control. The authors determined if measures of postural control and gait are predicted by state and trait physical and mental fatigue and energy, and how these relationships are modified by sex, sleep quality, and physical activity. Young adults (n = 119) completed the Modified Clinical Test of Sensory Integration, overground walking, and questionnaires to quantify fatigue and energy, sleep quality, and physical activity. Regression models indicated that trait fatigue, trait energy, and sleep quality were predictors of postural control (p ≤ .02, R2 ≥ .04). State fatigue, state energy, and sex were predictors of gait (p ≤ .05, R2 ≥ .03). While the variance explained was low (3-13%), the results demonstrate perceptions of fatigue and energy may influence posture and gait.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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