Bridging the gap between developmental systems theory and evolutionary developmental biology†
Bibliographic record
Abstract
Many scientists and philosophers of science are troubled by the relative isolation of developmental from evolutionary biology. Reconciling the science of development with the science of heredity preoccupied a minority of biologists for much of the twentieth century, but these efforts were not corporately successful. Mainly in the past fifteen years, however, these previously dispersed integrating programmes have been themselves synthesized and so reinvigorated. Two of these more recent synthesizing endeavours are evolutionary developmental biology (EDB, or "evo-devo") and developmental systems theory (DST). While the former is a bourgeoning and scientifically well-respected biological discipline, the same cannot be said of DST, which is virtually unknown among biologists. In this review, we provide overviews of DST and EDB, summarize their key tenets, examine how they relate to one another and to the study of epigenetics, and survey the impact that DST and EDB have had (and in future should have) on biological theory and practice.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".