Consumption of Bats (<em>Myotis</em> spp.) by Raccoons (<em>Procyon lotor</em>) During an Outbreak of White-Nose Syndrome in New Brunswick, Canada: Implications for Estimates of Bat Mortality
Bibliographic record
Abstract
Across their range, Raccoons (Procyon lotor) will opportunistically exploit bats (Chiroptera) roosting in caves as a source of food. During a significant mortality event associated with white-nose syndrome (WNS) at a cave in eastern Canada, we estimate that Raccoons consumed 3169–3827 dead and dying Little Brown Bats (Myotis lucifugus) and Northern Long-eared Bats (M. septentrionalis) infected with white-nose syndrome, equivalent to 62.0–74.9% of the total bat mortality at this site. However, the generally small dispersal distances of Raccoons and their reduced activity during the period when bats are hibernating suggest that Raccoons are likely not a significant vector for moving the fungus associated with white-nose syndrome, Geomyces destructans, between most caves at this latitude. Nevertheless, since we show that significant numbers of bats can be consumed in hibernacula through opportunistic feeding by Raccoons, estimates of in-cave mortality due to white-nose syndrome should incorporate any evidence of consumption of bats by Raccoons and other predators.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".