Hydro‐acoustic and tsunami waves generated by the 2012 <scp>H</scp>aida <scp>G</scp>waii earthquake: <scp>M</scp>odeling and in situ measurements
Bibliographic record
Abstract
Abstract Detection of low‐frequency hydro‐acoustic waves as precursor components of destructive tsunamis can enhance the promptness and the accuracy of Tsunami Early Warning Systems (TEWS). We reconstruct the hydro‐acoustic wave field generated by the 2012 Haida Gwaii tsunamigenic earthquake using a 2‐D horizontal numerical model based on the integration over the depth of the compressible fluid wave equation and considering a mild sloped rigid seabed. Spectral analysis of the wave field obtained at different water depths and distances from the source revealed the frequency range of low‐frequency elastic oscillations of sea water. The resulting 2‐D numerical model gave us the opportunity to study the hydro‐acoustic wave propagation in a large‐scale domain with available computers and to support the idea of deep‐sea observatory and data interpretation. The model provides satisfactory results, compared with in situ measurements, in the reproduction of the long‐gravitational waves. Differences between numerical results and field data are probably due to the lack of exact knowledge of sea bottom motion and to the rigid seabed approximation, indicating the need for further study of poro‐elastic bottom effects.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".