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Record W2152689849 · doi:10.1139/h05-034

Power training for older adults

2006· review· en· W2152689849 on OpenAlexaffvenue
Michelle M. Porter

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2006
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTraining (meteorology)Power (physics)PsychologyGerontologyMedicineGeography

Abstract

fetched live from OpenAlex

Resistance training is widely advocated for older adults to alleviate the muscle and strength loss that occurs with aging. While primary and secondary prevention of disability are often mentioned as benefits of strength training, the evidence for this is limited and inconclusive. Researchers have started to examine another form of resistance training that may prove to be more beneficial than strength training in terms of the reduction of age-related disability. Power training is being investigated because several studies have shown a stronger relationship between power and function than between strength and function. Early studies on power training suggest that neuromuscular power can be increased to a greater extent with high velocity or explosive training than strength training alone. In addition, there may be more positive effects on performance tasks measured in the laboratory, although evidence on disability reduction was very limited. Adverse events were reported in several studies, although the risk for injuries appears to be higher for testing than for training itself. Future well-designed studies on the risks and benefits of power training should provide more evidence on this promising form of resistance training for older adults of varying health and functional status.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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 designNot applicable
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

Citations83
Published2006
Admission routes2
Has abstractyes

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