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Record W7071888999

Validation of a game based rehabilitation platform for assessment of mobility and cognitive decline with age

2013· dissertation· en· W7071888999 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typedissertation
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNucleofectionArticular cartilage damageGestational periodDiafiltrationProteogenomicsHyporeflexiaTSG101
DOInot available

Abstract

fetched live from OpenAlex

The present study validates the Treadmill Rehabilitation Platform (TRP) protocol that assessed standing balance performance; spatial and temporal gait variability; stability measures and visual spatial cognitive task performances. Healthy individuals (mean age = 61.4± 4.4 years; n = 30) performed tasks from the TRP protocol while standing and while walking on treadmill. Moderate to High test retest reliability was observed for the TRP tool measures with a few exceptions. Standing balance decreased significantly as visual task load increased. Spatial and temporal gait variability increased whereas walking stability decreased significantly as visual task load increased. Visual task performance decreased significantly as physical load increased. In conclusion, the TRP protocol allows us to assess the ability to prioritize the division of attention when visual spatial cognitive tasks are performed while standing and during walking. Also, it allows reliable assessment of the effects of compromised attention during the tasks performances.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.325
Teacher spread0.298 · 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 designBench or experimental
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

Citations0
Published2013
Admission routes1
Has abstractyes

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