Automated<i>SKS</i>splitting and upper-mantle anisotropy beneath Canadian seismic stations
Bibliographic record
Abstract
We have developed an automated method for measuring shear wave splitting and applied it to SKS phases recorded at permanent broad-band stations in Canada. Our method performs two measurements, one seeking to minimize the energy on the transverse component, the other minimizing the smaller of two eigenvalues calculated from the covariance matrix of particle motion. A short-term-average/long-term-average (STA/LTA) phase picker is used to identify SKS arrivals and successive splitting measurements are made on incrementally larger windows around the SKS arrival. The final result is derived from the longest series of windows over which the splitting parameters remain constant. In this study we have processed over 20 000 station/event combinations from 34 stations and 1540 events. Roughly 2 per cent of the data produce reliable estimates of splitting, due to the stringent quality controls applied. We find good correlation between our results and previously published results from the same stations. At some stations we find significant differences in results between the two methods, an observation that has been verified using manual measurements. In each case, eigenvalue derived measurements are consistent with a single layer of anisotropy but transverse-energy derived results require a more complex interpretation. This discrepancy can be explained by misalignment of horizontal components. Tests with synthetic seismograms show that component misalignment can lead to false interpretations of multilayer or dipping anisotropy using the transverse-energy method. The quality of results at individual stations is variable, being influenced both by the volume of available data (determined by station deployment date and the distribution of natural seismicity), and the performance of the STA/LTA picker used to define the start of the SKS window. We compare the orientation of the inferred anisotropy at each station with local tectonic features and directions of absolute plate motion (APM); there is no consistent correlation. Many stations give results that agree with both, while some agree better with local geology and others agree better with APM directions. Results are available through a dedicated website and provide a potential aid to other studies of anisotropy in the deep Earth.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".