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Record W2509677929 · doi:10.1097/prs.0000000000002480

Current Uses of Botulinum Neurotoxins in Plastic Surgery

2016· review· en· W2509677929 on OpenAlexaff
Marie Noland, Donald H. Lalonde, Gilbert Yee, Rod J. Rohrich

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2016
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsNova Scotia Department of EnergySaint John Regional HospitalDalhousie University
Fundersnot available
KeywordsCurrent (fluid)Botulinum neurotoxinBiologyEngineeringMicrobiologyElectrical engineering

Abstract

fetched live from OpenAlex

LEARNING OBJECTIVES: After reading this article, the participant should be able to: 1. Recognize the various types of botulinum toxins and their differences. 2. Identify current indications, both approved and off-label. 3. Inject botulinum toxin to counteract various natural aging processes, including facial descent and rhytides. SUMMARY: Botulinum neurotoxin is a naturally synthesized microbial protein that has been applied in the management of various disorders. In particular, its application within the realm of plastic surgery is addressed in this article. After evaluating the medical literature, the seven indications with the highest quality trials for the use of botulinum neurotoxin in plastic surgery were as follows: rhytides, facial dystonias, facial nerve palsy and aberrant regeneration, hand tremor, palmar hyperhidrosis, neuropathic pain, and upper limb spasticity.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.068
GPT teacher head0.313
Teacher spread0.244 · 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 designOther design
Domainnot available
GenreReview

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

Citations22
Published2016
Admission routes1
Has abstractyes

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