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Record W72282465 · doi:10.1123/mcj.14.2.195

Effect of Working Memory and Spatial Attention Tasks on Gait in Healthy Young and Older Adults

2010· article· en· W72282465 on OpenAlexaff
Neelesh K. Nadkarni, Karl Zabjek, Betty Lee, William E. McIlroy, Sandra E. Black

Bibliographic record

VenueMotor Control · 2010
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsHeart and Stroke Foundation
FundersNational Institute on Aging
KeywordsSTRIDEWorking memoryGaitCognitionPhysical medicine and rehabilitationTask (project management)PsychologySpatial memoryEffects of sleep deprivation on cognitive performanceElementary cognitive taskAudiologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

Changes in gait parameters induced by the concomitant performance of one of two cognitive tasks activating working memory and spatial attention, was examined in healthy young adults (YA) and older adults (OA). There was a main effect of task condition on gait-speed (p = .02), stride-length (p < .001) and double-support time (p = .04) independent of the group. There were no significant differences between working memory and spatial attention associated gait changes. Working-memory and spatial-attention dual-tasking led to a decrease in gait-speed (p = .09 and 0.01) and stride-length (p = .04 and 0.01) and increase in double-support time (p = .01 and 0.03) in YA and decrease in stride-length (p = .04 and 0.01) alone in OA. Cognitive task associated changes in gait may be a function of limited attentional resources irrespective of the type of cognitive task.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.008
GPT teacher head0.300
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2010
Admission routes1
Has abstractyes

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