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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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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