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Record W4396764967 · doi:10.5435/jaaos-d-23-00650

Patellofemoral Instability Part II: Surgical Treatment

2024· review· en· W4396764967 on OpenAlexaff
Mitchell Bernstein, Isabella Bozzo, J. Patrick Park, Thierry Pauyo

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2024
Typereview
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineMedial patellofemoral ligamentOsteotomySoft tissueSurgeryCoronal planeFemurSurgical proceduresOrthopedic surgeryRadiology

Abstract

fetched live from OpenAlex

Treatment of patellofemoral instability in skeletally mature patients remains an important area of clinical and research interest. Both nonsurgical and surgical interventions are used to treat the underlying causes. Surgical management is the mainstay of treatment of recurrent PFI that fails nonsurgical treatment, and it is broadly classified into bony and soft-tissue procedures. Proximal bony procedures include femoral trochleoplasty, derotational osteotomies, and coronal alignment correction of the femur. Distal bony procedures include tibial tubercle transfer and derotational (supratubercle and infratubercle) osteotomies. Soft-tissue procedures consist of medial patellofemoral ligament repair or reconstruction and lateral lengthening procedures. This article is the second part of our two-article review on PFI, which focuses on surgical treatment options, their indications, outcomes, and potential complications.

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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.061
GPT teacher head0.324
Teacher spread0.263 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

Explore more

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