Tsunami data assimilation of Cascadia seafloor pressure gauge records from the 2012 Haida Gwaii earthquake
Bibliographic record
Abstract
Abstract We use tsunami waveforms recorded on a dense array of seafloor pressure gauges offshore Oregon and California from the 2012 Haida Gwaii, Canada, earthquake to simulate the performance of two different real‐time tsunami‐forecasting methods. In the first method, the tsunami source is first estimated by inversion of recorded tsunami waveforms. In the second method, the array data are assimilated to reproduce tsunami wavefields. These estimates can be used for forecasting tsunami on the coast. The dense seafloor array provides critical data for both methods to produce timeliness (>30 min lead time) and accuracy in both timing and amplitude (>94% confidence) tsunami forecasts. Real‐time tsunami data on dense arrays and data assimilation can be tested as a possible new generation tsunami warning system.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".