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Record W2077073188 · doi:10.1249/jsr.0b013e31829a74fd

Brain Health and Exercise in Older Adults

2013· review· en· W2077073188 on OpenAlexafffund
Michael A. Gregory, Dawn P. Gill, Robert J. Petrella

Bibliographic record

VenueCurrent Sports Medicine Reports · 2013
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsMedicineCognitionModalitiesPsychological interventionCognitive trainingAerobic exerciseGerontologyCognitive declineModality (human–computer interaction)Cognitive skillMEDLINEPhysical medicine and rehabilitationPhysical therapyPsychiatryDementiaDisease

Abstract

fetched live from OpenAlex

Identifying feasible and effective interventions aimed at mitigating the effects of cognitive decline in older adults is currently a high priority for researchers, clinicians, and policy makers. Evidence suggests that exercise and cognitive training benefit cognitive health in older adults; however, a preferred modality has to be endorsed yet by the scientific community. The purpose of this review is to discuss and critically examine the current state of knowledge concerning the effects of aerobic, resistance, cognitive, and novel dual-task exercise training interventions for the preservation or improvement of cognitive health in older adults. A review of the literature suggests that the potential exists for multiple exercise modalities to improve cognitive functioning in older adults. Nonetheless current limitations within the field need to be addressed prior to providing definitive recommendations concerning which exercise modality is most effective at improving or maintaining cognitive health in aging.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.415
Teacher spread0.368 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations56
Published2013
Admission routes2
Has abstractyes

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