Spatial variations of P wave attenuation in the mantle beneath North America
Bibliographic record
Abstract
We estimate the spatial variation of the seismic parameter t* using teleseismic (epicentral distance = 30°–85°) P wave spectra of about 200 deep (focal depths > 200 km) earthquakes recorded by 378 broadband seismometers in the United States and Canada. Relative P wave spectral ratios up to 1 Hz for about 63,000 station pairs with high signal‐to‐noise ratio and impulsive P waveforms are inverted for t*P by least squares inversion. The continental‐scale t*P pattern correlates to the age of geological terrains and the seismic, heat flow, gravity, and magnetic variations across North America. Predominantly low values of t*P are obtained in stable central North America (SNA), and high t*P values are obtained for stations in the tectonically active western part of the continent (TNA). This variation is similar to that observed previously in short‐period amplitude anomalies, spectral ratio variations, and ScS reverberations. On average, we resolve a contrast in t*P between SNA and TNA of about 0.2 s. We resolve regional variations in t*P, which correlate with tectonics. Relatively low t*P is associated with currently active subduction below Alaska. Relatively high t*P is found in SNA below the Appalachians and the Gulf Coast. The consistency between t*P and tectonics suggests that the observed variations in t*P are, on the scale of around 200–500 km, predominantly due to intrinsic attenuation. The similar patterns in t*P and predicted values for a recent global attenuation model confirm this further. The compatibility with the t*P computed for attenuation estimated via a thermal interpretation of shear wave velocity anomalies illustrates that variations in seismic velocity are predominantly due to physical effects with a strong attenuation signature, most likely temperature or a combination of temperature and water content.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".