NOAA efforts in monitoring of low-frequency sound in the global ocean
Bibliographic record
Abstract
Since August 1991, NOAA/PMEL has collected continuous recordings from the U.S. Navy SOSUS arrays in the North Pacific. In May 1996, this effort was expanded through the use of PMEL-developed autonomous hydrophones deployed in the eastern equatorial Pacific, and later to the central North Atlantic between 15N and 35N (March 1999), the Gulf of Alaska (October 1999), and the North Atlantic between 40N and 50N (June 2002). Natural seismicity in the Pacific produces nearly 10 000 events per year with source levels exceeding 200 dB (re: 1 micro-Pa @ 1 m), with about 3500 events per year exceeding this level in the North Atlantic. Significant contributions from manmade sources are present throughout the data but have not been quantified. Recordings from North Atlantic arrays are dominated by noise from seismic airgun profilers working offshore Canada, Brazil, and west Africa. In September 2001, a cabled vertical hydrophone array was installed at Pioneer Seamount, offshore central California, which will provide continuous, unclassified acoustic data (in the range of 1–450 Hz) to the research community in real time. Future plans call for the expansion of the NOAA monitoring effort to other opportunities worldwide and making the raw data available to the community via the Internet.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".