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Record W1992094176 · doi:10.1007/s11420-013-9345-9

Ultrasound-Guided Aspiration and Injection of an Intraneural Ganglion Cyst of the Common Peroneal Nerve

2013· article· en· W1992094176 on OpenAlexaff
Teresa Liang, Anukul Panu, Sean Crowther, Gavin Low, R. Lambert

Bibliographic record

VenueHSS Journal® The Musculoskeletal Journal of Hospital for Special Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of British Columbia
Fundersnot available
KeywordsMedicineGanglion cystCystFoot dropGanglionWeaknessSurgeryUltrasoundAnatomyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Intraneural ganglion cysts are rare, benign, mucinous lesions that occur within neural sheaths and are thought to involve cystic fluid exiting from nearby synovial joints. They often present as tender masses causing paresthesias in the distribution of the involved nerve, muscle weakness or cramping, or localized or referred pain. CASE DESCRIPTION: We present a case of a patient who initially presented with foot drop due to an intraneural ganglion cyst of the common peroneal nerve. This cyst was successfully treated using ultrasound guidance to aspirate the cyst and inject corticosteroid to prevent further inflammation. LITERATURE REVIEW: Standard of care has previously involved surgical resection, but this has been associated with a high frequency of recurrence. Due to the risks of nerve and vessel damage, there have been efforts to find alternative ways of resolving these cysts. PURPOSES AND CLINICAL RELEVANCE: Aspiration and injection of corticosteroid is a useful and minimally invasive alternative to surgery for managing intraneural ganglion cysts.

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)0.003
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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

Citations26
Published2013
Admission routes1
Has abstractyes

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