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Endoscopically Assisted Transconjunctival Approach in Orbital Medial Wall Fractures

2002· article· en· W2044967767 on OpenAlexaff
Goo‐Hyun Mun, Young Han Song, Sa Ik Bang

Bibliographic record

VenueAnnals of Plastic Surgery · 2002
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsJaneway Children's Health and Rehabilitation Centre
Fundersnot available
KeywordsMedicineEnophthalmosOrbital FractureReduction (mathematics)SurgeryMedial wallCoronal planeEndoscopeSoft tissueRadiologyDiplopia

Abstract

fetched live from OpenAlex

In Brief Full exposure of the medial orbital wall for fracture repair poses difficulty with traditional approaches except coronal incision, especially in cases of wide fracture. The endoscopic-assisted approach with limited incision has been introduced. The authors used the endoscopically assisted transconjunctival approach in 21 cases: 15 isolated medial orbital wall fractures and 6 cases of concomitant floor fractures. Through the medial transconjunctival slit incision, repair of the fracture using calvarial bone graft was undertaken with the aid of an endoscope. All patients recovered without any eye symptoms including clinically notable enophthalmos, but one immediate revisional operation was needed because of a displaced bone graft. Otherwise, the desired position of the graft was confirmed via computed tomography. The endoscopically assisted transconjunctival approach to the orbital medial wall provides improved surgical exposure of the most posterior and superior aspects of the fracture site, enabling more accurate reduction of orbital soft tissue and placement of bone grafts. Twenty-one medial orbital wall fractures were repaired with calvarial bone graft using an endoscope-assisted transconjunctival approach. No postoperative enophthalmos was observed, although one reoperation was required for a displaced bone graft.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.099
GPT teacher head0.302
Teacher spread0.202 · 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
Published2002
Admission routes1
Has abstractyes

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