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Record W6911067190 · doi:10.5061/dryad.nr60n

Data from: Females gain survival benefits from immune-boosting ejaculates

2016· dataset· en· W6911067190 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2016
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsImmune systemReproductionMatingImmunityPregnancyFunction (biology)

Abstract

fetched live from OpenAlex

Females in many animal taxa incur significant costs from mating in the form of injury or infection, which can drastically reduce survival. Therefore, immune function during reproduction can be important in determining lifetime fitness. Trade-offs between reproduction and immunity have been extensively studied, yet a growing number of studies demonstrate that mated females have a stronger immune response than virgins. Here, we use the Texas field cricket, Gryllus texensis, to test multiple hypotheses proposed to explain this post-mating increase in immune function. Using host-resistance tests, we found that courtship, copulation, and accessory fluids alone do not affect female immunity; rather, only females that acquire intact ejaculates containing testes-derived components exhibit significant increases in survival after exposure to bacterial pathogens. Our data suggest that male-derived components originating from an intact ejaculate and transferred to females during sex are required for the increased immune function characteristic of mated female crickets to occur.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.076
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0760.059

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 head0.085
GPT teacher head0.275
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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