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Record W2578933961 · doi:10.3390/toxins9010038

Historical Perspectives and Guidelines for Botulinum Neurotoxin Subtype Nomenclature

2017· review· en· W2578933961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueToxins · 2017
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsHealth Canada
FundersU.S. Army Medical Research Institute of Infectious DiseasesBiotechnology and Biological Sciences Research CouncilU.S. ArmyCenters for Disease Control and PreventionU.S. Department of Defense
KeywordsBotulinum neurotoxinNomenclatureNeurotoxinClostridium botulinumBiologyComputational biologyMedicineZoologyToxinTaxonomy (biology)GeneticsBiochemistry

Abstract

fetched live from OpenAlex

Botulinum neurotoxins are diverse proteins. They are currently represented by at least seven serotypes and more than 40 subtypes. New clostridial strains that produce novel neurotoxin variants are being identified with increasing frequency, which presents challenges when organizing the nomenclature surrounding these neurotoxins. Worldwide, researchers are faced with the possibility that toxins having identical sequences may be given different designations or novel toxins having unique sequences may be given the same designations on publication. In order to minimize these problems, an ad hoc committee consisting of over 20 researchers in the field of botulinum neurotoxin research was convened to discuss the clarification of the issues involved in botulinum neurotoxin nomenclature. This publication presents a historical overview of the issues and provides guidelines for botulinum neurotoxin subtype nomenclature in the future.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.264
GPT teacher head0.438
Teacher spread0.174 · 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