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Record W3198007785 · doi:10.3390/sym13091661

Acquired Facial, Maxillofacial, and Oral Asymmetries—A Review Highlighting Diagnosis and Management

2021· article· en· W3198007785 on OpenAlexaff
Janaki Iyer, Arvind Hariharan, Uyen M. N. Cao, Simon D. Tran

Bibliographic record

VenueSymmetry · 2021
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsMcGill University
Fundersnot available
KeywordsFacial symmetryMedicineCraniofacialMagnetic resonance imagingPsychosocialRadiographyOrthodonticsRadiology

Abstract

fetched live from OpenAlex

Facial asymmetry refers to the absence of, or the deviation from the regular mirror image of facial structures, relative to a referenced midline axis. It can be attributed to a wide spectrum of deformities, including congenital, developmental, or acquired conditions, which can originate either prenatally or postnatally. Though highly prevalent, asymmetry commonly goes undiagnosed due to its subtle or relative nature. Among the spectrum of conditions, acquired cases are triggered postnatally, in previously normal individuals, thus subjecting them to sudden, eventful psychological and psychosocial disharmony. When detected early, timely management may help intervene progressive growth of these conditions. This, therefore, emphasizes the need for a thorough diagnostic workup including medical/dental history, clinical examinations, study models, photographic and radiographic records for a case-by-case basis to prevent severe functional and aesthetic complications. Recently, advanced diagnostic procedures, such as stereophotogrammetry, 3D stereolithographic models, skeletal scintigraphy (radionucleotide scans), 3D computed tomographic scans, cone-beam computed tomography, and magnetic resonance imaging, have provided innovative diagnostic instruments for numerous craniofacial defects. This descriptive review aims at focusing on the factors leading to frequently encountered conditions of acquired facial asymmetry and highlights their clinical evaluation, conservative and surgical interventions by a multi-disciplinary team of clinicians.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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.

Study designNot applicable
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

Citations24
Published2021
Admission routes1
Has abstractyes

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