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Record W3154198944 · doi:10.1073/pnas.2023815118

Production, composition, and mode of action of the painful defensive venom produced by a limacodid caterpillar, <i>Doratifera vulnerans</i>

2021· article· en· W3154198944 on OpenAlexafffund
Andrew A. Walker, Samuel D. Robinson, Jean‐Paul Paluzzi, David J. Merritt, Samantha A. Nixon, Christina I. Schroeder, Jiayi Jin, M Goudarzi, Andrew C. Kotze, Zoltan Dekan, Andy Sombke, Paul F. Alewood, Bryan G. Fry, Marc E. Epstein, Irina Vetter, Glenn F. King

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomological Studies and Ecology
Canadian institutionsYork University
FundersNational Health and Medical Research CouncilWellcome TrustAustralian Research CouncilCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaUniversity of QueenslandWestpac Bicentennial Foundation
KeywordsVenomBiologyEnvenomationMode of actionPeptideBiochemistryScorpion VenomsInsectEcology

Abstract

fetched live from OpenAlex

Significance Venoms of limacodid caterpillars evolved independently to those of previously studied animals, and analysis of their venom therefore provides an opportunity to examine patterns of molecular convergence and divergence underlying the evolution of venom use. We report remarkable convergence in the recruitment of venom peptides between limacodids and other venomous taxa. Like scorpions and spiders, limacodids have weaponized immune system peptides to deter potential predators, although these cecropin-derived venom peptides are more similar in structure and mode of action to the venom peptides of hymenopteran insects. This study reveals a venom system with a unique combination of features not previously reported in other venomous animals and provides insights into the functional basis of venoms of the Limacodidae.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.268
Teacher spread0.233 · 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 designBench or experimental
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

Citations35
Published2021
Admission routes2
Has abstractyes

Explore more

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