Neighbourhood inversion of teleseismic<i>Ps</i>conversions for anisotropy and layer dip
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Bibliographic record
Abstract
The inversion of teleseismic receiver functions for lithospheric structure is difficult due to the non-linearity of the problem, which is greatly increased in the presence of dipping interfaces and layer anisotropy. Given an efficient ray-theoretical tool for forward-modelling teleseismic seismograms, we perform a directed Monte Carlo search technique using the neighbourhood algorithm of Sambridge, enabling us to search 20–30 parameters in a reasonable amount of computer time. Tests on synthetic data reveal inherent velocity–depth trade-offs in typical data sets, due to the limited moveout present in teleseismic Ps; the azimuth of the anisotropic symmetry axis and the strike of a dipping interface prove to be well-resolved given adequate backazimuthal coverage. We apply this technique to two single-station data sets. The first, from permanent station PGC, Vancouver Island, British Columbia, displays dipping low-velocity sediment layers in the mid-crust. The second, from a station at the northern end of the Tibetan plateau operating in 1991 and 1992, requires a sequence of thick crustal anisotropic layers to explain the observed pattern of receiver-function arrivals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it