MétaCan
Menu
Back to cohort
Record W4406896806 · doi:10.5435/jaaos-d-24-01219

Surgical Management of Meniscus Tears: Update on Indications and Techniques for Repair

2025· review· en· W4406896806 on OpenAlexaff
Derrick M. Knapik, Matthew V. Smith, Matthew J. Matava, Robert H. Brophy

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2025
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsMedicineTearsMeniscusSurgeryOsteoarthritisCartilageAnatomyPathology

Abstract

fetched live from OpenAlex

Because of the crucial role of the menisci in maintaining cartilage and joint health, meniscal tears affect the long-term health of the knee. Although partial meniscectomy has a role in the treatment of complex degenerative tears and tears with low healing capacity, advances in the concepts and understanding of meniscal repair, along with improvements in repair techniques and instrumentation, have expanded the indications for meniscal repair. With appropriate patient selection and preoperative planning, repair of meniscal tears can lower the rate of degenerative changes when compared with meniscectomy. The purpose of this review is to provide a concise overview of current repair indications, techniques, instrumentation, and outcomes for a variety of commonly encountered meniscal tears (radial, vertical, horizontal, oblique, ramp, root) in the knee.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.363
Teacher spread0.341 · 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 designNot applicable
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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of Orthopaedic SurgeonsSame topicKnee injuries and reconstruction techniquesFrench-language works237,207