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Record W2921367674 · doi:10.1016/j.jphys.2019.01.003

Appraisal of Clinical Practice Guideline: EULAR revised recommendations for the management of fibromyalgia

2019· article· en· W2921367674 on OpenAlexaff
Vanitha Arumugam, Joy C. MacDermid

Bibliographic record

VenueJournal of physiotherapy · 2019
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsSt Joseph's Health CentreWestern University
Fundersnot available
KeywordsMedicineFibromyalgiaGuidelinePhysical therapyClinical PracticePathology

Abstract

fetched live from OpenAlex

© 2019 Australian Physiotherapy Association. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). This clinical appraisal was originally published as: Arumugam, V. & MacDermid, J. C. (2019). Appraisal of Clinical Practice Guideline: EULAR revised recommendations for the management of fibromyalgia. Journal of Physiotherapy, 65(2), p. 112. DOI: https://doi.org/10.1016/j.jphys.2019.01.003

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)0.118
metaresearch head score (Gemma)0.398
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.118
Threshold uncertainty score0.627

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1180.398
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0080.013
Bibliometrics0.0120.010
Science and technology studies0.0050.004
Scholarly communication0.0140.006
Open science0.0110.008
Research integrity0.0280.020
Insufficient payload (model declined to judge)0.0080.008

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 head0.157
GPT teacher head0.581
Teacher spread0.424 · 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
GenreEmpirical

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

Citations2
Published2019
Admission routes1
Has abstractno

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