Apparent winterkill of Painted Turtle (<i>Chrysemys picta</i>)
Bibliographic record
Abstract
Around the margin of an artificial pond in Ottawa, Ontario, we found 25 Painted Turtles (Chrysemys picta) that appeared to have died over the course of two winters (17 during the first winter and eight during the second). We examined meteorological data to try to determine the cause of the mortality. Summer and fall rains were only slightly below normal in both years, suggesting water levels should have been close to normal. The winter air temperature was warmer than normal and winter snowfall was slightly above normal in both years. Unseasonable weather does not appear to be responsible for the winter mortality and the pond’s maximum depth of 1.7 m should prevent freezing to the bottom. It is possible that the artificial nature of the pond creates suboptimal overwintering habitat, rendering the site an ecological trap; however, there is no direct evidence to support this theory. It is also possible that winter mortality of turtles is widespread at temperate wetlands, but that dead turtles were more detectable at this site because of the bare shoreline around the pond. Winter mass mortality events, if common, may represent an additional threat to turtle populations, which are declining from various anthropogenic threats.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".