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Record W4406973766 · doi:10.1016/j.eats.2024.103396

Treatment of Failed Lateral Meniscal Oblique Radial Tear Repair With Segmental Allograft Meniscus Transplantation

2025· article· en· W4406973766 on OpenAlexaff
Mikalyn T. DeFoor, Emily Whicker, Marco Adriani, Ryan J. Whalen, Noah Knezic, Nate J Dickinson, Matthew T. Provencher

Bibliographic record

VenueArthroscopy Techniques · 2025
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineMeniscusSurgeryOblique caseTransplantationOptics

Abstract

fetched live from OpenAlex

Surgical techniques that preserve the native meniscus have been investigated in the setting of irreparable meniscal tears, including meniscal allograft transplantation (MAT) and meniscal synthetic scaffolds. Complete MAT removes the entirety of the native meniscal tissue for transplantation with suboptimal long-term survivorship. Similarly, synthetic meniscal scaffolds have shown variable success rates with an inability to regenerate functional tissue or prevent early osteoarthritis. Therefore, segmental MAT techniques have been explored to preserve the healthy, native meniscal biology and decrease knee contact pressures and total surface contact area. Current indications for segmental MAT continue to evolve but may be considered in near-complete or full-thickness segmental meniscal deficiency, generally 1 to 2.5 cm in total meniscal length. Typically, the segmental deficiency is in the posterior or posterior-middle junction of the meniscus. This technique article outlines an arthroscopic technique for lateral segmental meniscal transplantation for an irreparable lateral meniscal oblique radial tear of the posterior horn with a 20-mm segmental defect.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.005
GPT teacher head0.278
Teacher spread0.273 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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