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Record W4394893640 · doi:10.1097/gox.0000000000005749

Defining the Safe Entry Point in Deep Plane Facelifting with Novel Landmark for the Buccal Branch of the Facial Nerve

2024· article· en· W4394893640 on OpenAlexafffund
Ryan Alexander Medhurst, Cory Tremblay, Kristina Marrelli, Corliss Best, Lorraine Jadeski, Matthew Brace

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2024
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of TorontoUniversity of OttawaNOSM UniversityUniversity of Guelph
FundersUniversity of Ottawa
KeywordsCadaverAnatomical landmarkLandmarkFacial nerveAnatomyBuccal administrationMedicineIntersection (aeronautics)Artificial intelligenceComputer scienceDentistryCartographyGeography

Abstract

fetched live from OpenAlex

Background: In deep facial surgery, accurate preoperative landmarking of branches of the facial nerve is helpful in avoiding inadvertent facial nerve injury. The objective of our study was to determine the accuracy at which the intersection point of two bisecting lines that join facial surface landmarks can be used to accurately locate the buccal branch(es) of the facial nerve, specifically at the deep plane entry point (ie, intercept landmark). Methods: Thirty-three cadavers were dissected to determine the position of the buccal rami relative to the intercept. Results: Buccal rami crossed the intercept in 12.12% of specimens (0 mm from intercept, n = 4). Buccal rami passed superiorly in 66.67% of specimens (3.71 ± 3.28 mm from intercept, n = 7) and inferiorly in 21.21% of specimens (2.44 ± 0.92 mm from intercept, n = 7). Noteworthy, buccal rami were located within 1 cm of the intercept landmark with 96.97% accuracy (32/33 cadavers). Conclusions: These data suggest that this novel intercept (1) reliably locates the buccal branch of the facial nerve as it courses distal to the parotid gland, and (2) helps define a "safe zone" for entry into the deep plane where the likelihood of encountering the facial nerve is extremely low.

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)0.002
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 score0.287
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.279
Teacher spread0.262 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuePlastic & Reconstructive Surgery Global OpenSame topicFacial Rejuvenation and Surgery TechniquesFrench-language works237,207