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Record W2971786951 · doi:10.31542/j.muse.317

Immunity, Sex and Parasites: Does Sex of Sand-Field Cricket (Gryllus firmus) Affect Immune Response to Eugregarine Parasites?

2016· article· en· W2971786951 on OpenAlexaffvenue
Ashley Shaw

Bibliographic record

VenueMacEwan University Student eJournal · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMacEwan University
Fundersnot available
KeywordsParasite hostingBiologyCricketImmune systemParasite loadHost (biology)ZoologyParasitismImmunityImmunologyEcology

Abstract

fetched live from OpenAlex

There is controversy about the effects gut-dwelling eugregarine parasites have on their invertebrate hosts. If crickets (Gryllus firmus) apportion resources to reproduction differently in males vs. females, then resources used to mount immune responses to parasites may also differ – especially if the parasites are pathogenic. I investigated the possible differences in immune response between male and female crickets and attempted to determine whether these differences are related to intensity of parasitic infection. To do this, pieces of nylon filament were implanted into the hemocoel of crickets which tested the immune response where hemocytes surround the filament (encapsulation). These responses were compared to intensity of parasitic infection. No statistically significant relationship between sex and melanisation, or sex and parasite load were found. I found that the duration of melanization was negatively correlated to parasite abundance and that there was a positive correlation between body size and parasite number. This result suggests the existence of a relationship between the parasite and host that could be conflicting with sexual selection theory, such as host manipulation by the parasite.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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