Opportunistic Vessel-Based Detections of Migratory Bats in the Gulf of Maine
Bibliographic record
Abstract
Offshore wind energy is being pursued in the Gulf of Maine (Gulf) to reduce dependence on fossil fuels; yet wind turbines pose a collision risk for bats. Previous efforts to monitor bat activity in the Gulf have involved acoustic surveys from stationary platforms, such as buoys and islands. However, acoustic monitoring from vessels opportunistically transiting through the Gulf offers a promising method to capture bat activity further offshore and across both spatial and temporal gradients. To explore the utility of this approach and expand on the growing research on bat presence in the Gulf, acoustic bat detectors were deployed on marine vessels in the Gulf and collected data during periods from April through May and August through October 2024. A total of 69 offshore bat passes were recorded, including calls from Lasiurus cinereus (Hoary Bat), Lasionycteris noctivagans (Silver-haired Bat), and Lasiurus borealis (Eastern Red Bat). Eastern Red Bat and Silver-haired Bat detections were the furthest from shore (136 km and 169 km, respectively), indicating the presence of bats near offshore wind-lease areas during both spring and fall.
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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 | 0.000 | 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".