Springtime Emergence of Overwintering Toads,<i>Anaxyrus fowleri</i>, in Relation to Environmental Factors
Bibliographic record
Abstract
Although the timing of amphibians' spring emergence following winter dormancy may vary under the influence of climate change, the behavior of the animals should be more directly a response to the weather and/or other immediate stimuli and may be expected to show some population-level consistencies independent of timing. As such, there should be particular conditions of temperature, precipitation, wind, and/or phase of the lunar cycle at the onset of surface activity in a terrestrially hibernating anuran that may quantitatively differ from prior environmental conditions. Based on 24 years of data from a northern population of Fowler's Toads, we found that the springtime emergence of the toads is associated with increased temperature, relatively little rainfall or wind, and a gibbous moon. This remains true whether the toads emerge relatively early or late in spring. However, the toads' need for warmer temperatures to emerge for the first time in the year appears to significantly decrease the longer they have to wait. After emergence, though, the toads' activity during spring is positively associated with air temperature and negatively associated with wind speed, whereas rainfall and the illumination of the moon are not factors. Thus the environmental conditions necessary to evoke springtime emergence may not necessarily be the same as those that enable the animals' subsequent activity.
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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".