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Record W3128887540 · doi:10.1016/j.eats.2020.10.020

Soft‐Tissue Management and Neurovascular Protection During Opening‐Wedge High Tibial Osteotomy

2021· article· en· W3128887540 on OpenAlexaff
Kristian Kley, Hamid Rahmatullah Bin Abd Razak, Raghbir Khakha, Adrian J. Wilson, Ronald van Heerwaarden, Matthieu Ollivier

Bibliographic record

VenueArthroscopy Techniques · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsHigh tibial osteotomyNeurovascular bundleMedicineMedial collateral ligamentOsteoarthritisOsteotomySurgerySoft tissueCollateral damageWedge (geometry)Ligament

Abstract

fetched live from OpenAlex

Medial opening-wedge high tibial osteotomy (OW-HTO) is an excellent surgical option for patients with varus knee osteoarthritis. Medial collateral ligament (MCL) release and posterior neurovascular structure protection during OW-HTO are steps that often induce stress and nervousness during surgery, especially for surgeons in the earlier stages of their learning curve. While is it well-known that the MCL should be released during OW-HTO, the standard retraction techniques pose challenges in visualization and instrument placement in the surgical field. We present our technique, which illustrates an alternative method to manage the MCL and safely protect the neurovascular structures using a second and more posterior surgical window during OW-HTO.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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 designCase report
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

Citations18
Published2021
Admission routes1
Has abstractyes

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