Data from: Persistent directional selection on body size and a resolution to the paradox of stasis
Bibliographic record
Abstract
Directional selection on size is common but often fails to result in micro-evolution in the wild. Similarly, macro-evolutionary rates in size are low relative to the observed strength of selection in nature. We show that many estimates of selection on size have been measured on juveniles, not adults. Further, parents influence juvenile size by adjusting investment per offspring. In light of these observations, we help resolve this paradox by suggesting that the observed upward selection on size is balanced by selection against investment per offspring, resulting in little or no net selection gradient. We find that trade-offs between fecundity and juvenile size are common, consistent with the notion of selection against investment per offspring. We also find that median directional selection on size is positive for juveniles but no net directional selection exists for adult size. This is expected because parent-offspring conflict exists over size, and juvenile size is more strongly affected by investment per offspring than adult size. These findings provide qualitative support for the hypothesis that upward selection on size is balanced by selection against investment per offspring, where parent-offspring conflict over size is embodied in the opposing signs of the two selection gradients.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.018 |
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".