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Record W2994164135 · doi:10.3389/fnagi.2019.00329

Biological Sex: A Potential Moderator of Physical Activity Efficacy on Brain Health

2019· review· en· W2994164135 on OpenAlexafffund
Cindy K. Barha, Chun Liang Hsu, Lisanne ten Brinke, Teresa Liu‐Ambrose

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2019
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsVancouver Coastal HealthVancouver Coastal Health Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchFondation Brain CanadaAlzheimer's Association
KeywordsModerationPhysical activityPsychologyNeuroscienceBrain activity and meditationDevelopmental psychologyMedicinePhysical medicine and rehabilitationElectroencephalographySocial psychology

Abstract

fetched live from OpenAlex

The number of older people worldwide living with cognitive impairment and neurodegenerative diseases is growing at an unprecedented rate. Despite accumulating evidence that engaging in physical activity is a promising primary behavioral strategy to delay or avert the deleterious effects of aging on brain health, a large degree of variation exists in study findings. Thus, before physical activity and exercise can be prescribed as "medicine" for promoting brain health, it is imperative to understand how different biological factors can attenuate or amplify the effects of physical activity on cognition at the individual level. In this review article, we briefly discuss the current state of the literature, examining the relationship between physical activity and brain health in older adults and we present the argument that biological sex is a potent moderator of this relationship. Additionally, we highlight some of the potential neurobiological mechanisms underlying this sex difference for this relatively new and rapidly expanding line of research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.094
GPT teacher head0.410
Teacher spread0.315 · 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

Citations77
Published2019
Admission routes2
Has abstractyes

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