Nest substrate reflects incubation style in extant archosaurs with implications for dinosaur nesting habits
Bibliographic record
Abstract
Dinosaurs thrived and reproduced in various regions worldwide, including the Arctic. In order to understand their nesting in diverse or extreme environments, the relationships between nests, nesting environments, and incubation methods in extant archosaurs were investigated. Statistical analyses reveal that species of extant covered nesters (i.e., crocodylians and megapodes) preferentially select specific sediments/substrates as a function of their nesting style and incubation heat sources. Relationships between dinosaur eggs and the sediments in which they occur reveal that hadrosaurs and some sauropods (i.e., megaloolithid eggs) built organic-rich mound nests that relied on microbial decay for incubation, whereas other sauropods (i.e., faveoloolithid eggs) built sandy in-filled hole nests that relied on solar or potentially geothermal heat for incubation. Paleogeographic distribution of mound nests and sandy in-filled hole nests in dinosaurs reveals these nest types produced sufficient incubation heat to be successful up to mid latitudes (≤47°), 10° higher than covered nesters today. However, only mound nesting and likely brooding could have produced sufficient incubation heat for nesting above the polar circle (>66°). As a result, differences in nesting styles may have placed restrictions on the reproduction of dinosaurs and their dispersal at high latitudes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".