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Record W2727225549 · doi:10.1093/geroni/igx004.2646

CANADIAN GAIT AND BRAIN STUDY: COGNITION, GAIT AND THE RISK OF FALLING

2017· article· en· W2727225549 on OpenAlexaffabout
Manuel Montero‐Odasso

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsWestern University
Fundersnot available
KeywordsGaitPhysical medicine and rehabilitationFalling (accident)CognitionCognitive impairmentFear of fallingBalance (ability)Life expectancyFalls in older adultsFall preventionPsychologyPsychological interventionCognitive declineMedicineDiseaseGerontologyDementiaPoison controlInjury preventionPsychiatryMedical emergencyPopulation

Abstract

fetched live from OpenAlex

One of the main goals of geriatric medicine is to reduce the gap between overall life expectancy and disease free life expectancy. Two of the main contributors to this gap are increased rates of cognitive impairment and gait impairment. Older adults with cognitive impairment have a higher risk of falls, have twice the fall rates of cognitively normal older adults, and are notoriously resistant to fall prevention interventions. The precise mechanisms underlying the complex interplay between gait and cognitive impairment are poorly understood, and are the focus of the Gait and Brain Laboratory (The University of Western Ontario). This session will present evidence from the Canadian Gait and Brain Study showing that even mild cognitive impairment can affect gait and balance and the implications this has for fall prevention strategies in older adults with cognitive deficits.

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)0.001
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 score0.018
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.362
Teacher spread0.327 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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