Bone histology provides insights into the life history mechanisms underlying dwarfing in hipparionins
Bibliographic record
Abstract
Size shifts may be a by-product of alterations in life history traits driven by natural selection. Although this approach has been proposed for islands, it has not yet been explored in continental faunas. The trends towards size decrease experienced by some hipparionins constitute a good case study for the application of a life history framework to understand the size shifts on the continent. Here, we analysed bone microstructure to reconstruct the growth of some different-sized hipparionins from Greece and Spain. The two dwarfed lineages studied show different growth strategies. The Greek hipparions ceased growth early at a small size thus advancing maturity, whilst the slower-growing Spanish hipparion matured later at a small size. Based on predictive life history models, we suggest that high adult mortality was the likely selective force behind early maturity and associated size decrease in the Greek lineage. Conversely, we infer that resource limitation accompanied by high juvenile mortality triggered decrease in growth rate and a relative late maturity in the Spanish lineage. Our results provide evidence that different selective pressures can precipitate different changes in life history that lead to similar size shifts.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".