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Exercises for mechanical neck disorders

2015· review· en· W1575164208 on OpenAlexaff
Anita Gross, Theresa Kay, Jean-Philippe Paquin, Samuel Blanchette, P. Lalonde, Trevor Christie, G. Dupont, Nadine Graham, Stephen J Burnie, Geoff Gelley, Charles H. Goldsmith, Mario Forget, Jan L. Hoving, Gert Brønfort, Pasqualina Santaguida

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2015
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsGovernment of CanadaCanadian Armed ForcesSimon Fraser UniversityUniversity of ManitobaCanadian Memorial Chiropractic CollegeWestern UniversityUniversité LavalUniversity of TorontoUniversité du Québec à Trois-RivièresWomen's College HospitalMcMaster University
Fundersnot available
KeywordsMedicinePhysical therapyNeck painRandomized controlled trialCervicogenic headacheConfidence intervalQuality of life (healthcare)Meta-analysisData extractionMEDLINEPhysical medicine and rehabilitationBlindingSports medicineSurgeryCervical spineInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.002
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0250.002

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 head0.119
GPT teacher head0.420
Teacher spread0.301 · 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

Citations601
Published2015
Admission routes1
Has abstractyes

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