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Record W4221126403 · doi:10.1519/ssc.0000000000000719

Blood Flow Restriction Training for Individuals With Osteoarthritis

2022· article· en· W4221126403 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.

Bibliographic record

VenueStrength and conditioning journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBlood flow restrictionResistance trainingOsteoarthritisPhysical medicine and rehabilitationPhysical therapyMedicineStrength trainingPsychologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

ABSTRACT Research suggests that healthy eating and exercise decrease the likelihood of developing osteoarthritis (OA) with age. Despite this, OA is a prevalent chronic condition that typically causes joint pain at rest and during exercise, making it difficult to develop effective training programs. Recently, blood flow restriction (BFR) training has shown to be a beneficial alternative to traditional resistance training to improve muscle function. In this article, we provide a rationale as to how BFR may be a beneficial resistance training alternative that would allow individuals with osteoarthritis to experience similar improvements in muscle function compared with traditional resistance training using lower relative intensities.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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