Bibliographic record
Abstract
Seismograms recorded on the seafloor are affected by reverberations in the overlying ocean layer. We examine the feasibility of removing these reverberations through a 1D wave‐field decomposition based on a reflection–transmission formulation of the problem. Two decomposition schemes are presented. The first scheme involves a simple manipulation of the fundamental matrix relating stress and displacement of plane harmonic waves to upgoing and downgoing wavevector coefficients and requires measurement of both ocean bottom displacement and pressure. The second approach involves only displacement recordings and knowledge of the water column depth. This latter quantity will generally be known a priori from deployment logs, or, alternatively, it may be estimated using vertical displacement and pressure seismograms in a preprocessing step. Both approaches require prior information on seabed properties. In the case of P ‐wave incidence, the decomposition depends primarily on the seabed S velocity β . This quantity can be determined by examining trial decompositions over a range of β ’s and selecting the value that minimizes the energy of the upgoing S ‐wave component at the arrival time of the incident wave. We apply this approach to synthetic seismograms for a simple Earth structure and to recordings of two large events from the Central Oregon Locked Zone Array (COLZA) on the continental margin of Oregon. The real data indicate that the wave‐field decompositions are largely successful at lower frequencies (<0.1 Hz) but that 3D scattering, likely originating near the sediment–basement contact, is manifested at higher frequencies.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".