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Record W2019673515 · doi:10.1139/z01-044

On understanding variation in immune expression of the damselflies <i>Lestes</i> spp.

2001· article· en· W2019673515 on OpenAlexfundvenueno aff
Christopher P Yourth, Mark R. Forbes, Bruce P. Smith

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyImmune systemMiteInfestationZoologyParasitismSympatric speciationEcologyAcariImmunologyHost (biology)Botany

Abstract

fetched live from OpenAlex

Immune ability and immune expression have been viewed as life-history traits that are influenced by such factors as the likelihood of being parasitized, intensity and costs of parasitism, and trade-offs associated with immune expression. In this paper we show that different patterns of infestation by a generalist ectoparasite, Arrenurus planus Marshall (Arrenuridae: Hydrachnida), do not fully explain the variation in immune expression across four species of sympatric damselflies (Lestidae: Zygoptera). Within species, no gender biases in immune expression were evident. Whereas both males and females of one oft-exploited species did not mount immune responses against attending larval mites, males and females of three other species showed similar immune responses, with variable expression. The immune response was melanotic encapsulation of mite feeding tubes, and was associated with dead mites. Of the three species showing immune expression, the species with the highest prevalence and intensity of infestation had a significantly higher proportion of individuals responding immunologically to mites. In conclusion, current infestation levels only partially predict immune investment; consideration of the timing of emergence of different species suggests that season may be an important predictor of immune investment.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.725
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.033
GPT teacher head0.214
Teacher spread0.180 · 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 teacher head, 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

Citations48
Published2001
Admission routes2
Has abstractyes

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