Gregarious pupation act as a defensive mechanism against cannibalism and intraguild predation
Bibliographic record
Abstract
Coccinellid pupae use an array of defensive strategies against their natural enemies. This study aims to assess the efficiency of gregarious pupation as a defensive mechanism against intraguild predators and cannibals in coccinellid. The study was designed specifically (i) to determine the natural occurrence of gregarious pupation in the field for different coccinellid species, and (ii) to evaluate the adaptive value of gregarious pupation as a defensive mechanism against 2 types of predators (i.e., cannibals and intraguild predators). In the field, gregarious pupation consisted of a group of 2-5 pupae. The proportion of gregarious pupation observed varied according to species, the highest rate being observed with Harmonia axyridis Pallas (Coccinellidae; 14.17%). Gregarious pupation had no impact on the probability that intraguild predators and cannibals locate pupae. Intraguild predation occurred more often in site with gregarious pupation, while cannibalism occurred as often in site with gregarious pupation as in site with isolated pupa. However, for a specific pupa, the mortality rate was higher for isolated pupae than for pupae located in a gregarious pupation site both in the presence of intraguild predators and in the presence of cannibals. The spatial location of pupae within the group had no impact on mortality rate. Since it reduces the risk of predation, it is proposed that gregarious pupation act as a defensive mechanism for H. axyridis pupae.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".