A Cascadia Slab Model From Receiver Functions
Bibliographic record
Abstract
Abstract We map the characteristic signature of the subducting Juan de Fuca and Gorda plates along the entire Cascadia forearc from northern Vancouver Island, Canada, to Cape Mendocino in northern California, USA, using teleseismic receiver functions. The subducting oceanic crustal complex, possibly including subcreted material, is parameterized by three horizons capable of generating mode‐converted waves: a negative velocity contrast at the top of a low velocity zone underlain by two horizons representing positive contrasts. The amplitude of the conversions varies likely due to differences in composition and/or fluid content. We analyzed the slab signature for 298 long‐running land seismic stations, estimated the depth of the three interfaces through inverse modeling and fitted regularized spline surfaces through the station control points to construct a margin‐wide, double‐layered slab model. Crystalline terranes that act as the static backstop appear to form the major structural barrier that controls the slab morphology. Where the backstop recedes landward beneath the Olympic Peninsula and Cape Mendocino, the slab subducts sub‐horizontally, while the seaward‐protruding and thickened Siletz terrane beneath central Oregon causes steepening of the slab. A tight bend in slab morphology south of the Olympic Peninsula coincides with the location of recurring large intermediate depth earthquakes. The top‐to‐Moho thickness of the slab generally exceeds the thickness of the oceanic crust by 2–12 km, suggesting thickening of the slab or underplating of slab material to the overriding North American plate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".