One year of background underwater sound levels in Haro Strait, Puget Sound
Bibliographic record
Abstract
Haro Strait, on the west side of San Juan Island, WA, is the home range of the Southern Resident orca whales, a major shipping lane to and from Canada, and a center of private and commercial boating, especially in the summer. Four ITC hydrophones in a near-shore fixed array are used here to localize the underwater vocalizations of Southern Resident orca whales. The system operates 24 hours a day and has a frequency response of 100 Hz 10 kHz. Background sound levels are automatically characterized by half-hour reports that include: statistics and graphics based on mean sound levels (2-min running arithmetic mean pressure); a histogram of mean sound levels binned by frequency; and 2-s sound samples from maximum background events. Sound levels range from ∼90 dB re 1 microPa (quiet conditions) to ∼130 dB re 1 microPa when loud commercial ships are passing in the nearby shipping lane or speedboats are passing close to the hydrophone array. Complete results for one year of continuous monitoring will be presented, segmented by time (season, day of the week, hour in the day), frequency spectrum and dominant noise source class. [Work supported by 35 undergraduate researchers and the Colorado College.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".