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Record W2541041683 · doi:10.1097/dss.0000000000000896

Anatomy of the Cervicomental Region: Insights From an Anatomy Laboratory and Roundtable Discussion

2016· article· en· W2541041683 on OpenAlexaboutno aff
Jeffrey M. Kenkel, Derek Jones, Steven Fagien, Dee Anna Glaser, Gary D. Monheit, Karen Stauffer, Jonathan M. Sykes

Bibliographic record

VenueDermatologic Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeurovascular bundleAnatomyDissection (medical)Hyoid boneSternocleidomastoid muscle

Abstract

fetched live from OpenAlex

In 2015, ATX-101 (deoxycholic acid injection; Kybella in the United States and Belkyra in Canada; Kythera Biopharmaceuticals, Inc., Westlake Village, CA [an affiliate of Allergan plc, Dublin, Ireland]) was approved as a first-in-class injectable drug for reduction of submental fat. Use of a pharmacologic/injectable therapy within the submental region requires a thorough understanding of cervicomental anatomy to ensure proper injection technique and safe administration. To this end, an anatomy laboratory was conducted to review key external landmarks and important internal anatomic structures that characterize the lower face and anterior neck. External landmarks that define the boundaries of the cervicomental and submental regions were identified including the inferior mandibular border, the anterior border of the sternocleidomastoid muscle, the antegonial notch, the submental crease, the thyroid notch, and the hyoid bone. Relevant internal anatomic structures, including preplatysmal submental fat (the target tissue for ATX-101) and the platysma muscle as well as critical neurovascular and glandular tissues were revealed by dissection. Of particular interest was the marginal mandibular branch of the facial nerve because it typically courses along the inferior mandibular border near the proposed treatment area for ATX-101.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 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

Citations27
Published2016
Admission routes1
Has abstractyes

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