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Record W2780780910 · doi:10.1123/mc.2017-0040

Improvements in Obstacle Clearance Parameters and Reaction Time Over a Series of Obstacles Revealed After Five Repeated Testing Sessions in Older Adults

2017· article· en· W2780780910 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 · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsClearanceChoice reaction timeRepeated measures designPhysical medicine and rehabilitationSession (web analytics)MedicineSimulationMathematicsComputer sciencePhysical therapyStatisticsUrology

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate obstacle clearance and reaction time parameters when crossing a series of six obstacles in older adults. A second aim was to examine the repeated exposure of this testing protocol once per week for 5 weeks. In total, 10 older adults (five females; age: 67.0 ± 6.9 years) walked onto and over six obstacles of varying heights (range: 100-200 mm) while completing no reaction time, simple reaction time, and choice reaction time tasks once per week for 5 weeks. The highest obstacles elicited the lowest toe clearance, and the first three obstacles revealed smaller heel clearance compared with the last three obstacles. Dual tasking negatively impacted obstacle clearance parameters when information processing demands were high. Longer and less consistent time to completion was observed in Session 1 compared with Sessions 2-5. Finally, improvements in simple reaction time were displayed after Session 2, but choice reaction time gradually improved and did not reach a plateau after repeated testing.

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)0.001
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 score0.181
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.014
GPT teacher head0.300
Teacher spread0.287 · 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