The S receiver functions: synthetics and data example
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recently, the S receiver function method has been successfully developed to identify upper mantle interfaces. S receiver functions have the advantage of being free of S-wave multiple reflections and can be more suitable than P receiver functions for studying mantle lithosphere. However, because of specific ray geometry and interference of diverse phases, the S receiver function method has some technical difficulties and limitations. We use synthetic seismograms to demonstrate the feasibility and limitations of S receiver functions for studying mantle structures. Full-wavefield seismograms were calculated using the reflectivity method and processed to generate synthetic S receiver functions for S, SKS and ScS waves. Results show that S receiver functions can be obtained from waveforms of S, SKS and ScS waves. The synthetic S receiver functions for these incident waves show S-to-P converted phases at all discontinuities in the crust and upper mantle. Useful ranges of epicentral distances for calculation of S receiver functions are: 55°–85° for S, >85° for SKS and 50°–75° for ScS waves. We apply both the S and P receiver function methods to data recorded at broadband station YKW3 in Northwest Canada. The study shows that there is significant agreement among different receiver function methods, and demonstrates the usefulness of S receiver functions for imaging the mantle lithosphere.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it