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Record W4392377130 · doi:10.1097/gox.0000000000005650

Optimized Aesthetic Outcomes When Treating Glabellar Lines with Botulinum Toxin Type A: GLO 3 + 2: A Precise Technique Based on Anatomy

2024· article· en· W4392377130 on OpenAlexaff
Nowell Solish, Michael A. C. Kane, Jessica Brown, Conor J. Gallagher

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2024
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsUniversity of Toronto
FundersRevance
KeywordsEyebrowBotulinum toxinEyelidFacial musclesMedicineForeheadFrontalis musclePtosisAnatomyPosition (finance)OrthodonticsSurgery

Abstract

fetched live from OpenAlex

Good patient outcomes after treatment of the glabellar complex with botulinum toxin type A entail elimination of glabellar lines and maintenance of a natural eyebrow position. A precise injection technique that accurately targets the muscles that influence eyebrow position is required to reduce the risk of adverse aesthetic outcomes or unmasking an underlying eyelid ptosis. Here, we describe the glabellar lines optimization (GLO 3 + 2) injection anatomy technique, a precise five-point injection pattern that is based on current understanding of facial functional anatomy and which aims to minimize the risk of affecting nontargeted muscles. Injection sites above the brow or that do not target the precise location of the muscles in the glabellar complex are likely to inadvertently expose the frontalis to botulinum toxin type A and result in undesirable aesthetic outcomes. Because the frontalis is a strong determinant of aesthetic outcomes, it is important to consider the overall effects of the interactions between the eyebrow depressors and the opposing forces of the frontalis on brow outcomes in both the resting brow position and during dynamic brow movement.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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