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Record W1547366569 · doi:10.1111/jorc.12080

INTRA‐DIALYTIC EXERCISE TRAINING: A PRAGMATIC APPROACH

2014· review· en· W1547366569 on OpenAlexfundno aff
Sharlene A. Greenwood, P. Naish, Rachel Clark, Ellen O’Connor, Victoria A Pursey, Iain C. Macdougall, Thomas H. Mercer, Pelagia Koufaki

Bibliographic record

VenueJournal of Renal Care · 2014
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersReseau canadien de recherche respiratoireNational Institute for Health and Care Research
KeywordsMedicineRehabilitationExercise prescriptionPlan (archaeology)Physical therapyMedical educationPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

UNLABELLED: This continuing education paper outlines the skills and knowledge required to plan, implement and evaluate a pragmatic approach to intra-dialytic exercise training. AIM: The aim of this continuing education article is to enable the nephrology multi-disciplinary team (MDT) to plan, implement and evaluate the provision of intra-dialytic exercise training for patients receiving haemodialysis therapy. LEARNING OUTCOMES: After reading this article the reader should be able to: Appreciate the level of evidence base for the clinical effectiveness of renal exercise rehabilitation and locate credible sources of research and educational information Understand and consider the need for appropriate evaluation and assessment outcomes as part of a renal rehabilitation plan Understand the components of exercise programming and prescription as part of an integrated renal rehabilitation plan Develop a sustainable longer term exercise and physical activity plan.

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)0.047
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0020.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.327
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations34
Published2014
Admission routes1
Has abstractyes

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