Threshold-driven bifurcation in a stochastic predator–prey system with mode-switching and impulsive effects
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Bibliographic record
Abstract
A stochastic predator–prey system is developed to investigate the impacts of time-dependent switching, impulsive effects and anti-predator behavior. By the comparison principle and Itô formula, a key threshold [Formula: see text] is theoretically obtained, determining predator persistence or extinction. Based on this threshold, the dynamical bifurcations induced by switching and impulses are analyzed. Results reveal that switching may prevent extinction from strong anti-predator behavior but can also cause bifurcations, resulting in either predator persistence or extinction. Appropriate impulses can avoid extinction from switching and boost survival by inducing beneficial bifurcations. However, improper impulses, instead, may decrease population density, intensify population oscillations, and raise the extinction risk. The interaction between switching and impulses emphasizes the significance of coordinated interventions in reducing extinction risks and enhancing ecosystem stability.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it