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Record W2488104617 · doi:10.1136/bmj.i3934

Arthroscopic surgery for knee pain

2016· letter· en· W2488104617 on OpenAlexaff
Teppo L. N. Järvinen, Gordon Guyatt

Bibliographic record

VenueBMJ · 2016
Typeletter
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineKnee surgeryKnee arthroscopyKnee painArthroscopyMeniscusGeneral surgerySurgeryPlaceboEvidence-based medicinePhysical therapyRandomized controlled trialOsteoarthritisAlternative medicineIncidence (geometry)

Abstract

fetched live from OpenAlex

A highly questionable practice without supporting evidence of even moderate quality With 150 000 knee arthroscopies carried out in the United Kingdom each year, and about five times that number in the United States,1 2 arthroscopic partial meniscectomy—keyhole surgery for middle aged to older adults with knee pain to trim a torn meniscus—is one of the most common surgical procedures. Considering the enormous volume, it is natural to think that there is compelling evidence for the procedure being beneficial. Remarkably, this is not so. It is barely a decade since the publication of the first controlled trial addressing knee arthroscopy using placebo surgery as a comparator.3 Since then a series of rigorous trials, summarised in two recent systematic reviews and meta-analyses, provide compelling evidence that arthroscopic knee surgery offers little benefit for most patients with knee pain.4 5 The latest …

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.143
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.308
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations44
Published2016
Admission routes1
Has abstractyes

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