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Record W4237444385 · doi:10.1093/geront/gnv341.17

C-REACTIVE PROTEIN AND PHYSICAL PERFORMANCE IN ELDERLY POPULATIONS: RESULTS FROM THE IMIAS STUDY

2015· article· en· W4237444385 on OpenAlexaff
André Gustavo Pires de Sousa, Marı́a Victoria Zunzunegui, An Li, S Philips, J Gomez Monters, Jack M. Guralnik, Ricardo Oliveira Guerra

Bibliographic record

VenueThe Gerontologist · 2015
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsQueen's UniversityUniversité de Montréal
Fundersnot available
KeywordsC-reactive proteinPsychologyGerontologyMedicineInternal medicineInflammation

Abstract

fetched live from OpenAlex

given a letter).Analysis: The largest Lyapunov exponent (Lye) and approximate entropy (ApEn) were calculated to quantify the temporal structure of variability in ankle, knee, and hip joint angles.A mixed ANOVA was used to determine the interaction between groups and within subjects.Results: Structure of variability was significantly different between groups (Lye: ankle(p<.001),knee(p=.004),and hip(p<.001);ApEn: ankle(p<.001),knee(p=.005))with higher mean values in all instances in the older group.Only the young showed significant differences between conditions (Control to PF(p=.028) at ankle, WR to PF(p=.002) at ankle, knee(p=.009)and hip(p=.045)).Conclusions: Aging impacts the control of movements with older adults showing more randomness and greater divergence rates in their joint angle trajectories.Interestingly, older adults made no significant adjustments while dual-tasking which could indicate less adaptability in walking, especially during secondary tasks C-REACTIVE PROTEIN

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.126
GPT teacher head0.345
Teacher spread0.219 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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