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Record W2971167083 · doi:10.1097/moo.0000000000000573

Total nasal reconstruction: a review of the past and present, with a peak into the future

2019· review· en· W2971167083 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2019
Typereview
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsHotel Dieu HospitalQueen's University
Fundersnot available
KeywordsMedicineNoseTransplantationSurgeryReconstructive SurgeonFacial reconstructionForehead

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The goal of this article is to review the complex topic of total nasal reconstruction and present a wide range of options for completing this difficult surgical procedure. RECENT FINDINGS: Nasal reconstruction has a long history dating back thousands of years. Some historical techniques still exist today, including the paramedian forehead flap. The introduction of free tissue transfer and other pedicled flaps has provided multiple options for the reconstructive surgeon. The future of nasal reconstruction will include facial transplantation and likely bioengineered tissues. SUMMARY: The principles of nasal reconstruction have gone unchanged for decades; however, the techniques to meet the principles have. The current reconstructive methods of grafts, free flaps, and pedicled flaps used to replace lining, structure, and skin will likely be used for several years to come. However, the use of facial transplantation has proved effective and bioengineered tissues present an exciting future for organ replacement.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.685
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.052
GPT teacher head0.359
Teacher spread0.307 · 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