Hibernation phenology of<scp><i>M</i></scp><i>yotis lucifugus</i>
Bibliographic record
Abstract
Abstract Hibernating animals must time immergence and emergence carefully to maximize reproductive success and reduce the risk of encountering inclement weather or predators. Few studies of phenology exist for any hibernating species and those that do address species which mate during spring. We used passive transponders ( PIT tags) to study hibernation phenology of little brown bats M yotis lucifugus , a species that mates prior to hibernation in the fall. We expected that adult females would emerge earliest as early parturition increases juvenile survival. We predicted that females with large fat stores should emerge earliest because of their ability to tolerate inclement spring weather at the maternity roost. We also predicted that adult males would remain active later than females to maximize mating opportunities and compensate for body mass decline during the mating period. We implanted 475 bats with PIT tags and remotely recorded immergence and emergence timing at a hibernaculum in central C anada. As expected, adult males were active significantly later (median immergence date = 16 S eptember 2011) than adult females (11 S eptember 2011) and adult females emerged earlier (median emergence date = 6 M ay 2012) than both adult males (25 M ay 2012) and subadults (13 M ay 2012). Emergence timing was correlated with fall body condition in adult females, with fatter females emerging earlier, but not males. Our results highlight the importance of reproductive timing as an influence on hibernation phenology of mammals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".