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Facts and myths pertaining to fibromyalgia

2018· review· en· W2983082431 on OpenAlexaff
Winfried Häuser, Mary‐Ann Fitzcharles

Bibliographic record

VenueDialogues in Clinical Neuroscience · 2018
Typereview
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsFibromyalgiaMilnacipranPregabalinDuloxetinePain disorderPsychiatryDiseaseNeurologyMedicineChronic painDepression (economics)CognitionChronic fatigue syndromePsychologyPhysical therapyClinical psychologyAlternative medicineAnxietyInternal medicineAntidepressant

Abstract

fetched live from OpenAlex

Fibromyalgia (FM) is characterized by chronic widespread pain, unrefreshing sleep, physical exhaustion, and cognitive difficulties. It occurs in all populations throughout the world, with prevalence between 2% and 4% in general populations. Definition, pathogenesis, diagnosis, and treatment of FM remain points of contention, with some even contesting its existence. The various classification systems according to pain medicine, psychiatry, and neurology (pain disease; persistent somatoform pain disorder; masked depression; somatic symptom disorder; small fiber neuropathy; brain disease) mostly capture only some components of this complex and heterogeneous disorder. The diagnosis can be established in most cases by a general practitioner when the symptoms meet recognized criteria and a somatic disease sufficiently explaining the symptoms is excluded. Evidence-based interdisciplinary guidelines give a strong recommendation for aerobic exercise and cognitive behavioral therapies. Drug therapy is not mandatory. Only a minority of patients experience substantial symptom relief with duloxetine, milnacipran, and pregabalin.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.002

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 head0.257
GPT teacher head0.482
Teacher spread0.225 · 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

Citations215
Published2018
Admission routes1
Has abstractyes

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Same venueDialogues in Clinical NeuroscienceSame topicFibromyalgia and Chronic Fatigue Syndrome ResearchFrench-language works237,207