Global threshold dynamics of a spatial chemotactic mosquito-borne disease model
Bibliographic record
Abstract
Abstract It is natural that mosquitoes move towards high human population density and environmental heterogeneity plays a pivotal role in disease transmission, and thus we formulate and analyse a mosquito-borne disease model with chemotaxis and spatial heterogeneity. The global existence and boundedness of solutions are proven to guarantee the solvability of the model and is challenging due to the model complexity. Under appropriate conditions, we demonstrate that the disease-free equilibrium is globally asymptotically stable provided that the basic reproduction number $\mathcal{R}_0$ is less than one, and the system is uniformly persistent and admits at least one endemic equilibrium if $\mathcal{R}_0$ is greater than one. Furthermore, we numerically explore the impacts of chemotactic effect, spatial heterogeneity and dispersal rates of infected individuals to provide a clear picture on disease severity. In particular, the mosquito chemotaxis causes mild disease in some regions but severe in others, which suggests developing targeted strategies to control mosquitoes in specific locations and achieve a deep understanding on the chemotaxis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".