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Record W4210517893 · doi:10.1002/14651858.cd015074

Non-pharmacological interventions for fibromyalgia (fibromyalgia syndrome) in adults: an overview of Cochrane Reviews

2022· article· en· W4210517893 on OpenAlexaff
Winfried Häuser, Emma Fisher, Serge Perrot, Andrew Moore, Souzi Makri, Julia Bidonde

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2022
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSystematic reviewPsychological interventionMedicineFibromyalgiaCochrane collaborationAdverse effectPhysical therapyInclusion and exclusion criteriaMEDLINEProtocol (science)Alternative medicineCochrane LibraryIntensive care medicinePsychiatryPharmacologyPathology

Abstract

fetched live from OpenAlex

This is a protocol for a Cochrane Review (overview). The objectives are as follows: To summarise the evidence on the effectiveness, acceptability, and safety of non‐pharmacological interventions for FMS in adults. To explore variability in methods across Cochrane Reviews, in regards to inclusion/exclusion criteria, outcomes, comparisons, and the methods of assessment of adverse events. To examine the quality of Cochrane Reviews of FMS and inform on how reporting of Cochrane Reviews on FMS may be improved.

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)0.018
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.044
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.008
Bibliometrics0.0190.018
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.160
GPT teacher head0.436
Teacher spread0.276 · 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 designSystematic review
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

Citations8
Published2022
Admission routes1
Has abstractyes

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