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Record W3152624348 · doi:10.1016/j.jpain.2021.03.147

Non-Surgical Interventions for Lumbar Spinal Stenosis Leading To Neurogenic Claudication: A Clinical Practice Guideline

2021· article· en· W3152624348 on OpenAlexafffund
André Bussières, Carol Cancelliere, Carlo Ammendolia, Christine Comer, Fadi Al Zoubi, Claude-Édouard Châtillon, Greg Chernish, James M. Cox, Jordan A. Gliedt, Danielle Haskett, Rikke Krüger Jensen, Andrée-Anne Marchand, Christy Tomkins‐Lane, Julie O’Shaughnessy, Steven Passmore, Michael Schneider, Peter Shipka, Gregory W. Stewart, Kent Stuber, Albert Yee, Joseph Ornelas

Bibliographic record

VenueJournal of Pain · 2021
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsAlberco Construction (Canada)Research ManitobaUniversity of ManitobaWilliam Osler Health SystemCanadian Memorial Chiropractic CollegeBone and Joint CanadaGDG EnvironnementUniversité du Québec à Trois-RivièresMount Royal UniversityOntario Tech UniversityCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecMcGill UniversityUniversity of TorontoMount Sinai HospitalUniversité du Québec à Montréal
FundersNational Institute for Health and Care ResearchUniversity of Ontario Institute of TechnologyMcGill University
KeywordsMedicineNeurogenic claudicationPhysical therapyGuidelineRandomized controlled trialPopulationLow back painQuality of life (healthcare)Manual therapyEvidence-based practiceRehabilitationPhysical medicine and rehabilitationLumbar spinal stenosisEvidence-based medicineSystematic reviewMEDLINELumbarSurgeryAlternative medicineNursing

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.106
GPT teacher head0.485
Teacher spread0.379 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations100
Published2021
Admission routes2
Has abstractno

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