AMPlifying bat monitoring across North America: an online portal shares acoustic data to advance bat conservation across the continent
Bibliographic record
Abstract
Each year, wildlife biologists deploy thousands of echolocation detectors to monitor bat activity and find out what species are present at a site. But pulling these results together in a single place could help us learn more about broader scale patterns of bat activity and their seasonal movements. A new tool, the Bat Acoustic Monitoring Visualization Tool (https://visualize.batamp.databasin.org/), helps to do just that. Since its inception in 2013, users have contributed over 200,000 nights of detector data to BatAMP resulting in an unprecedented collection of results that allows users to track when and where species are detected across the U.S. and Canada. Through ongoing data uploads by a growing set of contributors as well as a planned integration to visualize acoustic data generated via the North American Bat Monitoring Program, this tool will greatly expand our understanding of the seasonal occurrence of bats and how those may change over time.
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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 | 0.000 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".