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Record W2312984508 · doi:10.1017/s0031182016000305

Mite choice generates sex- and size-biased infection in<i>Drosophila hydei</i>

2016· article· en· W2312984508 on OpenAlexaff
Erin O. Campbell, Lien T. Luong

Bibliographic record

VenueParasitology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyDrosophila (subgenus)MiteEvolutionary biologyGeneticsZoologyEcologyGene

Abstract

fetched live from OpenAlex

Heterogeneities in parasite infection among conspecific hosts often manifest as sex- or size-biased infections, which are typically attributed to differential host susceptibility and exposure. Since parasite fitness is often tied to host quality, host preference by parasites is likely to be under strong selection. We test the hypothesis that host preference is sufficient to generate variability in infection rate among conspecifics. Specifically, we ask whether the mite Macrocheles muscaedomesticae is able to discriminate between Drosophila hydei hosts of different sex and size, while explicitly accounting for the potential confounding effects of these two factors. Our results indicate a preference for female hosts, but this preference appears to be driven by size and not sex per se. When differences in body size were controlled for, the sex-biased infection disappeared, while mites presented with the choice of two female flies of disparate sizes were more likely to select the larger host. Across the distribution of fly body weight in this study, mites preferentially attached to flies of intermediate size. This study provides evidence that mite choice for certain host types can play an important role in parasite transmission, even in the absence of differential susceptibility or exposure among hosts.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.410

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 head0.026
GPT teacher head0.295
Teacher spread0.269 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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