Body temperature fluctuations in free-ranging eastern foxsnakes (<i>Elaphe gloydi</i>) during cold-water swimming
Bibliographic record
Abstract
We examined the thermal biology of free-ranging terrestrial eastern foxsnakes (Elaphe gloydi Conant, 1940) that were voluntarily swimming in cold water during spring, in Georgian Bay, Ontario, Canada. Using temperature-sensitive radiotelemetry, we recorded body temperatures of foxsnakes during 12 cold-water swims, and subsequent warming on shore. During these swims, water temperatures were from 11 to 22 °C and distances of 85–1330 m were travelled. Snakes that were in cold water long enough equilibrated with water temperature and did not maintain a body temperature above ambient. The largest observed drop in body temperature was 22.6 °C (over 11 min) and the largest increase was 23 °C (over 66 min). Such large, rapid temperature fluctuations have not previously been reported in detail from snakes in the field. Twice as many telemetry observations as expected occurred between 1200 and 1400, suggesting that snakes chose to swim midday. Additionally, our results suggest that foxsnakes bask to raise their body temperature prior to swimming in cold water. We compared swimming speed and the coefficient of temperature change among foxsnakes and other snake species. Swimming speed was positively correlated with water temperature, similar to other findings. We found no clear trend between mass and the coefficients of cooling and warming; however, snakes cooled in water 2.8–8.6 times faster than they warmed in air.
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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".