An update to real-time observations of the impact of COVID-19 on underwater sound
Bibliographic record
Abstract
A slowdown in global trade activity due to COVID-19 has led to a reduction in commercial shipping traffic into the Port of Vancouver. The Ocean Networks Canada observatory system provides researchers real-time access to oceanographic data from a wide range of instruments including hydrophones located along the offshore and inshore approaches to Vancouver. Power spectral density statistics at 100 Hz from four of these bottom mounted hydrophones were monitored, along with AIS data and shipping and trade statistics to assess to what extent the economic impact of COVID-19 can be observed acoustically and in near real-time. The quarterly trend in median weekly noise power in the shipping band of frequencies provides an early indicator that a reduction in noise commensurate with the economic slowdown occurred at two hydrophone stations. Time series of the median and 1st percentile weekly power provide a retrospective detail of the impact of the pandemic on underwater sound.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".