Fear as an enemy? Behavioral changes of <i>Ananteris mauryi</i> (Scorpiones: Buthidae) triggered by chemical cues from an intraguild predator
Bibliographic record
Abstract
Fear level and intraguild predation are factors that act together to directly influence animal behavior, population dynamics, and community structure. These factors trigger stress, which promotes behavioral, morphological, physiological, and demographic changes, especially in the prey. Some invertebrates, such as scorpions, are known to have a refined chemoreception system to perceive both prey and predators. Therefore, we investigated the ability of an intraguild prey, the scorpion Ananteris mauryi Lourenço, 1982, to detect chemical traces of its predator, the scorpion Tityus pusillus Pocock, 1893. Our goal was to verify whether A. mauryi exhibits antipredator behavior induced exclusively by chemical cues from its predator. Ananteris mauryi specimens were subjected to two experimental treatments: one with and one without traces of T. pusillus. The results showed that A. mauryi tended to avoid substrates with chemical traces of T. pusillus, confirming its capacity for chemical detection. As a result of this perception, changes in behavioral frequencies were triggered, generating an antipredator behavioral repertoire. These findings were supported by behavioral changes, such as tail wagging, which is performed exclusively by scorpions in the presence of a predator and at imminent risk of predation.
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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 | 0.000 | 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".