Going, going, gone: the impact of white-nose syndrome on the summer activity of the little brown bat ( <i>Myotis lucifugus</i> )
Bibliographic record
Abstract
Since its discovery in the winter of 2005-2006, white-nose syndrome (WNS) has killed over one million little brown bats (Myotis lucifugus) in the American northeast. Although many studies have reported die-offs of bats at winter hibernacula, it is important to understand how bat mortality linked to WNS at winter hibernacula affects bat activity levels in their summer ranges. In the summer (May-August) of 2007, 2008 and 2009, we recorded echolocation calls to determine bat activity at sites along the Hudson River, NY (within approx. 100 km of where WNS was first reported). We documented a 78 per cent decline in the summer activity of M. lucifugus, coinciding with the arrival and spread of WNS. We suggest that mortality of M. lucifugus in winter hibernacula is reflected by reduced levels of activity in the summer and that WNS affects the entire bat population of an area, and not only individual hibernacula.
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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 | 0.001 |
| 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) | 0.001 | 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".