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Record W2104770587 · doi:10.1249/jsr.0b013e3181e7da73

Uncomplicated Resistance Training and Health-Related Outcomes

2010· review· en· W2104770587 on OpenAlex

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

VenueCurrent Sports Medicine Reports · 2010
Typereview
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsMedicineResistance trainingExercise prescriptionAffect (linguistics)Medical prescriptionAerobic exercisePhysical therapyDiseasePhysical medicine and rehabilitationStrength trainingDiabetes mellitusIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

Compared to aerobic training (AT), resistance training (RT) has received far less attention as a prescription for general health. However, RT is as effective as AT in lowering risk for cardiovascular disease, diabetes, and other diseases. There is a clear ability of RT, in contrast to AT, to promote gains, maintenance, or slow loss of skeletal muscle mass/strength. Thus, as an antisarcopenic exercise treatment, RT is of greater benefit than AT; given the aging of our population, this is of primary importance. In our view, a substantial barrier to greater adoption of RT is the incorrectly perceived importance of variables such as external load, intensity, and volume, leading to complex, difficult-to-follow regimes. We propose a more feasible and easier-to-adhere-to paradigm for RT that could affect how RT is viewed and adopted as a prescription for public health.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.158
GPT teacher head0.429
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