Short-Period Surface-Wave Tomography in the Continental United States—A Resource for Research
Bibliographic record
Abstract
Abstract The variation of phase and group velocity dispersion of Love and Rayleigh waves was determined for the continental United States and adjacent Canada. By processing ambient noise from the broadband channels of the Transportable Array (TA) of USArray and several Program for the Array Seismic Studies of the Continental Lithosphere experiments and using some earthquake recordings, the effort was focused on determining dispersion down to periods as short as 2 s. The relatively short distances between TA stations permitted the use of a 25 km×25 km grid for the four independent tomographic inversions (Love and Rayleigh and phase and group velocity). One reason for trying to obtain short-period dispersion was to have a data set capable of constraining upper crust velocity models for use in determining regional moment tensors. The benefit of focusing on short-period dispersion is apparent in the tomography maps—shallow geologic structures such as the Mid-Continent Rift, and the Michigan, Illinois, Anadarko, Arkoma, and Appalachian basins are imaged. In our processing, we noted that the phase velocities were more robustly determined than the group velocities. We also noted that the inability to obtain dispersion at short periods shows distinct regional patterns that may be related to the local upper crust structure.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".