Temperature Does Not Affect Hatch Timing in Snapping Turtles (Chelydra serpentina)
Bibliographic record
Abstract
Many oviparous species rely on hatching cues to ensure hatchlings maximize their survival, given the external environmental conditions. In nature, these cues are traditionally environmental (e.g., temperature) or social (e.g., communication between embryos). Examples of both are common throughout ectothermic taxa, particularly reptiles. In the present study, we explored the role of temperature in hatch timing in Snapping Turtles (Chelydra serpentina). We allowed embryos to incubate in wild nests for the majority of embryonic development, then isolated embryos in the lab, and maintained them at 24°C until they reached Yntema stage 25. At this developmental stage, external morphological differentiation is complete and yolk resorption begins. We then incubated embryos until pipping across a range of constant but biologically relevant temperatures (20, 23, 25, 28, or 30.5°C). To test whether thermal variance acts as a hatching cue, we also included a treatment in which temperature fluctuated diurnally around a stationary mean (25 ± 4°C). We found that the timing of egg pipping was not related to temperature treatment, thermal fluctuation, or sex of the embryo. Thus, contrary to traditional understanding, temperatures in the range studied do not affect the duration of the final embryonic stage in C. serpentina embryos, and a definitive hatching cue in this species is yet unknown.
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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 | 0.000 |
| 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) | 0.001 | 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".