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Record W7132527218

A useful flap combination in wide and complex defect reconstruction of the medial canthal region: Glabellar rotation and nasolabial V-Y advancement flaps

2015· article· en· W7132527218 on OpenAlexaboutno aff
Kesiktas E., Eser C., Gencel E., Aslaner E.E.

Bibliographic record

VenueÇukurova University Institutional Repository · 2015
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEyelidRotation flapPlastic surgeryLigamentCanthusNasolabial fold
DOInot available

Abstract

fetched live from OpenAlex

Background: Reconstruction of medial canthal defects after tumour excision is difficult owing to the thin skin of the region and the concavity of the anatomical landmarks, which enclose complex structures such as the medial canthal ligament and the lacrimal system. Local reconstruction methods for this region include secondary healing, full-thickness skin grafts, and skin flaps from the frontal, transnasal, glabellar and upper eyelid regions. Objective: To demonstrate a useful combination of two local flaps in wide defects of the medial canthal region. Methods: Between 1998 and 2012, a combination of glabellar rotation and nasolabial V-Y advancement flaps were used in 11 patients with wide complex defects after excision, including periosteum, of invasive basal cell carcinoma. Results : All patients were tumour free and underwent functional and aesthetic reconstruction of the medial canthal region. There were no major complications, and no relapses were observed. Conclusion: This technique achieves good match in colour and texture, and has satisfactory results both aesthetically and functionally. In addition, donor area morbidity is minimal and surgical technique is simple. © 2015 Canadian Society of Plastic Surgeons.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.026
GPT teacher head0.226
Teacher spread0.200 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueÇukurova University Institutional RepositorySame topicReconstructive Facial Surgery TechniquesFrench-language works237,207