A Double Difference Tomography Study of the Washington Forearc: Does Siletzia Control Crustal Seismicity?
Bibliographic record
Abstract
Abstract We present new seismic tomography of the Washington forearc using a suite of manually picked regional earthquake phase arrivals. The recovery of similarly sampled P and S velocity permits the robust calculation of Poisson's ratio throughout the region. The seismological signature of Siletzia, an accreted oceanic plateau that crops out in Washington as the Crescent Formation, is evident in our models as a continuous high Poisson's ratio body that coincides with subsurface structures estimated from potential field maps. Relocated earthquakes preferentially locate in low Poisson's ratio regions in the forearc crust and, in particular, in a diffuse layer located at 15–25 km depth in the crust beneath relatively aseismic Siletzia. Our imaging of the Puget Sound is consistent with previous interpretations of the architecture of major faults and blocks, as evident by distinct Poisson's ratio signatures that distinguish sedimentary basins from mafic rocks of the Crescent Formation. We speculate that seismicity below the Puget Sound is promoted by slab‐derived fluids that are localized beneath Siletzia as a result of intrinsic low vertical permeability.
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 | 0.000 | 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".