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Record W2262470837 · doi:10.1177/229255031101900404

Hyaluronic Acid Used for the Correction of Nasal Deviation in An 18-Year-Old Middle Eastern Man

2011· article· en· W2262470837 on OpenAlexaffvenue
JR Piggott, Arjang Yazdani

Bibliographic record

VenueCanadian Journal of Plastic Surgery · 2011
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineContouringHyaluronic acidFiller (materials)RhinoplastyNoseSoft tissueDeformityDentistryNasal boneSurgeryAnatomyComposite material

Abstract

fetched live from OpenAlex

The use of fillers for nonsurgical rhinoplasty has advanced in both materials and methods, and continues to gain popularity in North America. This technique is most often used for secondary revisions, although reports of fillers used in primary rhinoplasty in selected patients have been recently described. The present report details the use of a hyaluronic acid dermal filler in a young Middle Eastern man for a post-traumatic crooked nose deformity. Primary correction of the patient's right-sided nasal bone deviation using hyaluronic acid as a soft tissue filler was achieved with excellent results and patient satisfaction. The current use of fillers in nasal contouring is reviewed.

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 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)0.001
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 score0.019
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.094
GPT teacher head0.254
Teacher spread0.160 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2011
Admission routes2
Has abstractyes

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