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Record W2122926304 · doi:10.1177/229255031001800409

Reconstruction of a Full-Thickness Alar Wound Using An Auricular Conchal Composite Graft

2010· article· en· W2122926304 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Plastic Surgery · 2010
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNasotracheal intubationSurgeryDeformityIntubation

Abstract

fetched live from OpenAlex

Nasogastric intubation has become a frequently used method for alleviating gastrointestinal symptoms. Necrosis from alar pressure during prolonged nasogastric and nasotracheal intubation is common, and can result in considerable deformity if it is unrecognized. The reconstruction of full-thickness alar wounds often requires multiple challenging surgical procedures. Difficult full-thickness alar defects often require nasal mucosal replacement for lining, cartilage batten graft support for the preservation of nasal function, and skin coverage for the restoration of an aesthetically correct appearance. Free composite conchal grafting can offer a single-staged, one-step repair of difficult full-thickness alar wounds that are no larger than 1.5 cm in size. A thorough explanation of the graft design and execution is presented, as well as a case report and literature review. Free composite conchal grafting can produce aesthetic and functional results that rival the most sophisticated flap reconstructions of the lateral ala.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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