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Record W2159275154

Auricular reconstruction for microtia: A review of available methods.

2014· review· en· W2159275154 on OpenAlexaff
Narges Baluch, Satoru Nagata, Chul Park, Gordon H. Wilkes, John F. Reinisch, Leila Kasrai, David M. Fisher

Bibliographic record

VenuePubMed · 2014
Typereview
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsSickKids FoundationSt Joseph's Health CentreUniversity of TorontoUniversity of AlbertaHospital for Sick Children
Fundersnot available
KeywordsMedicineMicrotiaBreast reconstructionCostal cartilageSurgeryImplantHumanitiesCartilageAnatomyArtBreast cancer
DOInot available

Abstract

fetched live from OpenAlex

Several surgical techniques have been described for auricular reconstruction. Autologous reconstruction using costal cartilage is the most widely accepted technique of microtia repair. However, other techniques have certain indications and should be discussed with patients and families when planning for an auricular reconstruction. In the present review, the authors discuss the main surgical techniques for auricular reconstruction including autologous costal cartilage graft, Medpor (Stryker, USA) implant and prosthetic reconstruction. To further elaborate on the advantages and disadvantages of each technique, the authors invited leaders in this field, Dr Nagata, Dr Park, Dr Reinisch and Dr Wilkes, to comment on their own technique and provide examples of their methods.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.108
GPT teacher head0.380
Teacher spread0.273 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations101
Published2014
Admission routes1
Has abstractyes

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