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Record W2078903790 · doi:10.1139/h04-027

Natural Killer Cells and Exercise Training in the Elderly: A Review

2004· review· en· W2078903790 on OpenAlex
Jennifer M. Dipenta, Julia M. Green-Johnson, René J.L. Murphy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2004
Typereview
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsAcadia University
FundersNatural Sciences and Engineering Research Council of CanadaNova Scotia Health Research Foundation
KeywordsImmunosenescenceNatural killer cellImmunologyImmune systemInnate immune systemNatural (archaeology)Cell functionPopulationMedicineGerontologyBiologyCellPsychologyCytotoxic T cellEnvironmental health

Abstract

fetched live from OpenAlex

Consistent reports of the positive relationship between regular physical activity and immunosenescence have generated much excitement in the field of exercise immunology. It is generally accepted that natural killer (NK) cell activity per NK cell decreases with age; decreases in NKCA have been associated with infection and death in the aged. The effects of exercise and training on natural killer cells, components of the innate immune system, have been studied extensively in young people. However, the published research on the elderly population is limited. Generally it has been found that training increases or does not change natural killer cell activity or counts in the elderly. The clinical relevance of these results is yet to be fully explored. In addition, the limitations of these studies on immune function have been many, and studies are often difficult to compare due to differences in their methods and presentation of results.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.313
Teacher spread0.271 · 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