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Record W3017939841 · doi:10.1097/jsa.0000000000000278

Lateral Extra-articular Tenodesis in Anterior Cruciate Ligament Reconstruction

2020· review· en· W3017939841 on OpenAlexaff
Alan Getgood, Gilbert Moatshe

Bibliographic record

VenueSports Medicine and Arthroscopy Review · 2020
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsFowler Kennedy Sport Medicine Clinic
Fundersnot available
KeywordsMedicineBiomechanicsAnterior cruciate ligament reconstructionAnterolateral ligamentAnterior cruciate ligamentLigamentOrthodonticsAnatomySurgeryPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

A subset of patients have residual rotational laxity following anterior cruciate ligament reconstruction (ACLR) despite the evolution of ACLR techniques. In recent years, there has been increased interest in addressing residual laxity because it is associated with poor outcomes after ACLR. There is an expanding body of knowledge on the anatomy and biomechanics of the anterolateral soft tissue restraints in regard to their rotational control of the knee and this has reignited an interest in extra-articular reconstruction techniques for augmenting ACLR. Reconstruction techniques currently used can be broadly categorized as either lateral extra-articular tenodesis or anterolateral ligament reconstruction. In this review, we discuss the relevant anatomy, biomechanics, and rationale behind the indications and technique of our current extra-articular augmentation procedure.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.002

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 head0.033
GPT teacher head0.355
Teacher spread0.322 · 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

Citations25
Published2020
Admission routes1
Has abstractyes

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