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Record W2292146502 · doi:10.1177/1203475415587211

Crescentic Back Cut

2015· article· en· W2292146502 on OpenAlexaff
Eiman Nasseri, Christian Murray

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRotation flapSurgeryFibrous jointCheekRotation (mathematics)Artificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Facial reconstruction requires the use of various techniques to repair cutaneous defects. Sliding flaps, such as advancement and rotation flaps, typically result in tension alterations and skin redundancy, necessitating a secondary defect. OBJECTIVE: We describe a back cut technique that allows minimization of the scar line and appropriate placement of tension vectors in certain locations, which we call the crescentic back cut. METHODS: A patient with a surgical defect on his preauricular cheek is repaired by use of a rotation flap modified with a crescentic back cut. We briefly review the alternative methods for management of flap/defect discrepancies in rotation flaps. RESULTS: The crescentic back cut is simple to suture, can be adjusted in length and thickness to minimize pedicle transection, and keeps the scar short and within the relaxed skin tension lines. CONCLUSION: The crescentic back cut is a useful option to manage flap/defect discrepancies in rotation flaps.

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: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.064
GPT teacher head0.308
Teacher spread0.244 · 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
GenreMethods

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

Citations3
Published2015
Admission routes1
Has abstractyes

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