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Record W2687028970 · doi:10.1002/9781118661833.ch1

History of Botulinum Toxin for Medical and Aesthetic Use

2017· other· en· W2687028970 on OpenAlexaff
Alastair Carruthers, Jean Carruthers

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsSKiN HealthUniversity of British Columbia
Fundersnot available
KeywordsBotulismMedicineBotulinum toxinClostridium botulinumBotulinum neurotoxinDysphagiaTrismusAnesthesiaSurgeryToxinChemistry

Abstract

fetched live from OpenAlex

The district medical officer and poet, Dr. Justinus “Wurst” Kerner, was considered the godfather of botulinum toxin (BoNT) research for his early, intensive work. In his monograph, Kerner described the symptoms of botulism — including vomiting, intestinal spasms, mydriasis, ptosis, dysphagia, and respiratory failure — and recommended methods for the treatment and prevention of food poisoning. The bacterium Clostridium botulinum is identified as the causative agent of botulism. The follow-up discovery in the mid-1950s that BoNT blocks the release of acetylcholine from motor nerve endings when injected into hyperactive muscles led to a renewed interest in the neurotoxin as a potential therapeutic agent. BoNT is used increasingly in combination with other facial rejuvenation procedures. BoNT is also used during surgery to prolong or enhance the aesthetic results and as an aid in wound healing and minimizing scars.

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)0.000
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0530.020

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 head0.033
GPT teacher head0.278
Teacher spread0.246 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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