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Record W4382752275 · doi:10.1016/j.jseint.2023.05.005

Author response—nonoperative treatment of lateral epicondylitis: a systematic review and meta-analysis

2023· review· en· W4382752275 on OpenAlexaff
Peter Lapner, Jonah Hébert‐Davies, J. Whitcomb Pollock, Ana Alfonso-Fernández, Jonathan Marsh, Graham J.W. King

Bibliographic record

VenueJSES International · 2023
Typereview
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsSt Joseph's Health CareWestern UniversityUniversity of ManitobaOttawa HospitalPan Am ClinicUniversity of Ottawa
Fundersnot available
KeywordsEpicondylitisMeta-analysisMedicineSystematic reviewMEDLINESurgeryInternal medicineElbowPolitical science

Abstract

fetched live from OpenAlex

We accept that lateral epicondylitis may be a degenerative condition and that inflammation may or may not be present. Although “lateral elbow tendinopathy” is acceptable, the term “lateral epicondylitis” remains in widespread use in the medical literature and in trials included in this study, and the term we chose to describe the condition for the purposes of our study.

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)0.016
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.118
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0100.004
Insufficient payload (model declined to judge)0.0390.006

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 head0.235
GPT teacher head0.479
Teacher spread0.244 · 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 designMeta-analysis
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

Citations0
Published2023
Admission routes1
Has abstractyes

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