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Record W2187906784

2012 Canadian Guidelines for the diagnosis and management of fibromyalgia syndrome

2012· article· en· W2187906784 on OpenAlexaffabout
Mary‐Ann Fitzcharles, Peter A. Ste‐Marie, Don L. Goldenberg, Susan Abbey, Manon Choinière, Gordon Ko, Dwight E. Moulin, Pantelis Panopalis, Johanne Proulx, Yoram Shir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineLibrary scienceFibromyalgiaFamily medicineUniversity hospitalGerontologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

1 Division of Rheumatology, McGill University, Montreal, Quebec, Canada Alan Edwards Pain Management Unit, McGill University Health Center, Montreal, Quebec, Canada Faculty of Law, Universite de Montreal, Montreal, Quebec, Canada Division of Rheumatology, Tufts University School of Medicine, Boston, Massachusetts, USA Faculty of Medicine, University of Calgary, Alberta, Canada Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada Centre de la recherche du Centre hospitalier de l’Universite de Montreal; Department of Anesthesiology, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, Canada Division of Physiatry, University of Toronto, Toronto, Ontario, Canada Departments of Clinical Neurological Sciences and Oncology, University of Western Ontario, London, Ontario, Canada Patient representative

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)0.005
metaresearch head score (Gemma)0.020
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: Methods · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0080.007
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0060.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0130.004

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 head0.102
GPT teacher head0.366
Teacher spread0.263 · 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
GenreMethods

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

Citations39
Published2012
Admission routes2
Has abstractyes

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