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Record W2128981346 · doi:10.1123/japa.13.3.239

Gender-Related Differences in Physical Performance among Seniors

2005· article· en· W2128981346 on OpenAlexaff
Kristin E. Musselman, Brenda Brouwer

Bibliographic record

VenueJournal of Aging and Physical Activity · 2005
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsQueen's University
Fundersnot available
KeywordsBalance (ability)Confidence intervalBody mass indexPhysical medicine and rehabilitationGaitPhysical therapyPhysical activityPsychologyAnalysis of varianceMedicinePreferred walking speedMuscle strengthConcentricMathematics

Abstract

fetched live from OpenAlex

This study examined gender differences in balance, gait, and muscle performance in seniors and identified gender-specific factors contributing to physical performance. Forty (20 men, 20 women) healthy, community-dwelling seniors (74.5 +/- 5.3 years) participated. Limits of stability, gait speed, lower limb flexor and extensor isokinetic concentric peak torques, self-reported activity level, and balance confidence were measured. No gender differences were detected in gait speed, limits of stability when normalized to height, activity level, or balance confidence (p = .188). Women were weaker than men (p = .007), even after controlling for weight and body-mass index, suggesting that other gender-related factors contribute to strength. Gender accounted for 18-46% of the variance in strength and served as a modifier of the relationship between activity level and strength in some muscle groups. The primary factors relating to gender-specific strength was activity level in men and body weight in women.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.342
Teacher spread0.311 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

Explore more

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