Long-term marine mammal occurrence in the Distributed Biological Observatory 2010–2015
Bibliographic record
Abstract
The Distributed Biological Observatory (DBO) is a set of eight biological hotspot areas spanning latitudinally from the Northern Bering Sea to the Canadian Beaufort Sea. The DBO is an international collaboration between researchers from the United States, Japan, Canada, China, South Korea, and Russia that work in the Alaskan Bering, Chukchi, and Beaufort Seas; all research vessels passing through one of the DBO regions collect biophysical data (i.e., temperature, salinity, sea ice concentration and thickness, chlorophyll, nutrients, and zooplankton occurrence) along a pre-described line of sampling stations. Since the pilot study in 2010, and with funding from the Bureau of Ocean Energy Management (BOEM), the Marine Mammal Laboratory at the Alaska Fisheries Science Center of NOAA has maintained passive acoustic recorder moorings at two of the DBO regions, colocated with oceanographic moorings from the Pacific Marine Science Center (P. Stabeno). This coverage was expanded to five DBO regions in 2012, again with colocated oceanographic moorings at four of the sites. Here, an interannual comparison of the long-term mooring results from gray, bowhead, beluga, humpback, and killer whales, walrus, ribbon and bearded seals, and vessel and seismic airgun noise will be presented and compared with the sampled biophysical data.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".