Bibliographic record
Abstract
ABSTRACT. The evolutionary stability concepts continuously stable strategies (CSS) and evolutionarily stable neighborhood invader strategies (ESNIS) share two properties in common. First, they are both evolutionarily stable strategies (ESS). Secondly, given any strategy in the close neighborhood of the CSS or ESNIS, there are some strategies that are closer to the CSS or ESNIS that can invade it. An ESNIS is a CSS but the converse is not true in general. We examine evolutionary adaptive dynamics in the neighborhood of a CSS that is not an ESNIS. We show that if an evolutionary game possesses a CSS which is not an ESNIS, the succession of strategies mediated by natural selection become arbitrarily close to the CSS but the precise value of the CSS cannot be attained unless the CSS is the first strategy to invade into the environment and is henceforth never perturbed. Thus if evolution does not start with the CSS that is not an ESNIS, we will have a phenomenon of bounded evolutionary succession that does not come to an end. The analysis is applied to a class of monomorphic population evolutionary game models in which species ecological interaction is modeled by the Lotka‐Volterra equations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".