Interplay of resource mappings and evolutionary diffusion: Competitive exclusion and coexistence analysis
Bibliographic record
Abstract
We study a directed dynamical reaction–diffusion model with no-flux boundary conditions where two populations interact in a spatial heterogeneous closed environment state. Both populations growths are proportional to the same growth law, but the dispersal policies with the migration coefficients differ. The population is diffusing according to their resource functions, and the carrying capacity is bounded in a heterogeneous habitat. This paper’s main results are: if the dispersion functions are non-proportional, then the coexistence is not possible unless the whole environment is homogeneous; and in case of proportionality, the species shows similar behavior. The coexistence is possible if the resource phase and the distribution function of a second organism are identical and non-constant. A few numerical examples verify that the extinction of one species by the other and the coexistence are visible in a non-homogeneous environment.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".