Bibliographic record
Abstract
Review of: Dercole, F. and S. Rinaldi. 2008. Analysis of Evolutionary Processes: The Adaptive Dynamics Approach and its Applications. Princeton University Press. 333 pp. ISBN: 978‐0‐691‐12006‐5. $65.00 (cloth) Recent years have witnessed an explosion of interest among evolutionary biologists in a modeling technique known as adaptive dynamics. In some ways this modeling technique has raised considerable controversy (see Waxman and Gavrilets 2005 and related replies in the same issue). In my view, the controversy is not over its utility, because there can be little doubt that it has provided interesting and important new insights into a variety of topics in evolutionary biology. Rather, some of the controversy has centered on the assumptions made in this modeling approach (e.g., separation of timescales, rates of mutation, etc.). Although these criticisms have some validity, they are really no more damning to the technique of adaptive dynamics than are analogous criticisms to the techniques of game theory, population genetics, and other modeling approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".