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Immune response to nylon filaments in two damselfly species that differ in their resistance to ectoparasitic mites

2011· article· en· W2088645220 on OpenAlexafffund
Laura Nagel, Julia J. Mlynarek, Mark R. Forbes

Bibliographic record

VenueEcological Entomology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsBiologyDamselflyImmune systemOdonataZoologyArthropodPredationMiteEcologyImmunology

Abstract

fetched live from OpenAlex

1. Insects commonly resist parasites using melanotic encapsulation. Many studies measuring immune response use the amount of melanin deposited on an artificial object that has been inserted into the animal as a proxy of the amount of resistance that the host is capable of mounting to natural parasites. 2. The relevance of this methodology to immune response in natural insect populations needs further study. Here, we examined two temperate damselfly species to elucidate the relationships among damselfly size, natural resistance to mites, and the immune response mounted by the same damselflies against nylon filaments. 3. The damselfly species that had high rates of melanotic encapsulation of mites in nature deposited more melanin on the nylon inserts than the species with low rates of natural resistance. 4. In females of this species, those that had resisted mites naturally melanised the nylon filament more aggressively than those that did not resist mites. 5. Our results show some support for the use of nylon filaments to assess natural patterns of immune response in these damselflies, but also suggest that caution should be used in interpreting the responses.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.053
GPT teacher head0.270
Teacher spread0.217 · 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 designObservational
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

Citations27
Published2011
Admission routes2
Has abstractyes

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