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Record W2252705048 · doi:10.1177/2513826x1500100201

Bilateral Erosion of Malar Implants Into the Maxillary Sinuses

2015· article· en· W2252705048 on OpenAlexvenueno aff
Elizabeth L. Dale, Larry A. Sargent

Bibliographic record

VenuePlastic Surgery Case Studies · 2015
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFixation (population genetics)SinusitisDentistrySurgeryImplantMaxillary sinusComplicationPopulation

Abstract

fetched live from OpenAlex

Augmentation malarplasty is a cosmetic procedure rarely associated with complications; however, some reported complications are severe. The authors describe a case of missed diagnosis in a patient with chronic sinusitis secondary to erosion of malar implants into the maxillary sinuses. A review of the literature demonstrates that all severe complications of implant-based malar augmentation involve bone erosion and occur many years after initial placement. Silicone implants may have a higher risk for bone erosion and severe complications; however, it is not clear whether this risk is only associated with implants that have not been adequately fixed to the underlying bone. Surgeons should ensure that implants will not move from their original location, and screw fixation is the most reliable method for this purpose. Patients undergoing augmentation malarplasty should be informed of this potential complication so that lengthy workups and unnecessary treatments can be avoided.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.092
GPT teacher head0.325
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

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 designCase report
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

Citations2
Published2015
Admission routes1
Has abstractyes

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