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Record W7096287323

Commentary

2007· article· en· W7096287323 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSarcopeniaMuscle massMuscle atrophyMuscle strengthAtrophyIndependence (probability theory)Psychological interventionResistance training
DOInot available

Abstract

fetched live from OpenAlex

All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association. The preservation of functional independence in elderlypeople depends on the ability to maintain musclemass, strength and balance. Sarcopenia refers to the age-related declines in muscle mass and function and is as-sociated with an increased risk of falls, fractures and frailty.1 The cause of sarcopenia is multifactorial, and suggested mechanisms include declines in local growth factors (e.g., insulin-like growth factor), mitochondrial dysfunction, mus-cle-fibre atrophy and the loss of functioning motor units.1,2 Various interventions have been used to target the decline in muscle strength in elderly people. Resistance exercise train-ing and the use of nutritional supplementation have been shown to significantly improve muscle mass and function.3,4 However, it is often difficult for elderly people to sustain these types of exercise programs, which has prompted the exploration of other interventions.

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)0.003
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0140.010
Insufficient payload (model declined to judge)0.0940.043

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 head0.048
GPT teacher head0.397
Teacher spread0.349 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2007
Admission routes1
Has abstractyes

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