Does Host Value Influence Female Aggressiveness, Contest Outcome and Fitness Gain in Parasitoids?
Bibliographic record
Abstract
Abstract Intraspecific competition for resources is common in animals and may lead to physical contests. Contest outcomes and aggressiveness can be influenced by the resource holding potential of contestants but also by their perception of the resource value (RV). Competitors may assess resource quality directly (real RV) but may also estimate it according to their physiological status and their experience of the habitat quality (subjective RV). In this article, we studied contests between females of the solitary parasitoidPachycrepoideus vindemmiaeRondani (Hymenoptera: Pteromalidae) when exploiting simultaneously a host, aDelia radicumL. (Diptera: Anthomyiidae) pupa. We tested the effect of factors modifying host value on the occurrence of agonistic behaviours, contest outcomes and host exploitation. The factors tested were: the quality of the previous habitat experienced by females, female egg load, host parasitism status and the stage reached by the owner female in her behavioural oviposition sequence. Females successfully protected their host against intruders during its exploitation, but not after oviposition, and their aggressiveness did not seem to be influenced by their perception of the RV. The fact that the host is subsequently parasitized by the opponent females appears to mainly depend on the host selectiveness of females.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".