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Record W2517320336 · doi:10.1007/s00586-008-0623-z

Methods for the Best Evidence Synthesis on Neck Pain and Its Associated Disorders

2008· article· en· W2517320336 on OpenAlexaff
Linda Carroll, J. David Cassidy, Paul M. Peloso, Lori Giles‐Smith, C. Sam Cheng, Stephen W. Greenhalgh, Scott Haldeman, Gabrielle van der Velde, Eric L. Hurwitz, Pierre Côté, Margareta Nordin, Sheilah Hogg‐Johnson, Lena W. Holm, Jaime Guzmán, Eugene J. Carragee

Bibliographic record

VenueEuropean Spine Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of British ColumbiaDouglas CollegeInstitute for Work & HealthToronto Western HospitalUniversity of ManitobaUniversity Health NetworkUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsMedicineNeck painSystematic reviewScientific evidenceEvidence-based medicinePsychological interventionBest practiceBest evidenceEvidence-based practiceMandateMEDLINEPhysical therapyAlternative medicineIntensive care medicinePsychiatryPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.166
metaresearch head score (Gemma)0.448
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score0.878

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1660.448
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0240.033
Bibliometrics0.0270.016
Science and technology studies0.0020.003
Scholarly communication0.0090.005
Open science0.0060.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0570.004

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 head0.044
GPT teacher head0.355
Teacher spread0.311 · 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.

Study designNot applicable
DomainMethods
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

Citations6
Published2008
Admission routes1
Has abstractno

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