Offshore Acoustic Monitoring of Bats in the Gulf of Maine
Bibliographic record
Abstract
Although bats have been observed from offshore ships, are known to cross large bodies of water, and have been observed seasonally on remote islands, little information has been collected regarding their distribution, species composition, and behavior at offshore locations. Techniques for monitoring bats over long periods are limited, and the typical logistical constraints for studies of nocturnal, flying species are amplified in open-water habitats. To our knowledge, this acoustic study represents the first attempt to monitor bats on a regional scale in an offshore environment. Long-term acoustic monitoring of 16 sites in the Gulf of Maine confirmed the presence of long-distance migratory and cave-hibernating bat species at coastal sites; large, forested islands; small, isolated rocks lacking woody vegetation; and an offshore weather buoy. Patterns of presence, species composition, and activity were highly variable among sites but consistently indicated that bats were most active and widespread between mid-August and mid-September, and that bats regularly occurred offshore. Sporadic presence of certain species during this period, surrounded by multiple nights with no activity, also suggests that bat presence offshore may be associated with migratory flight or use of remote islands as temporary roosts or stopover sites during seasonal movements.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".