Geostatistical inversion of seismic and GPR reflection images: what can we actually resolve?
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
Estimation of the spatial statistics of subsurface velocity heterogeneity from surface‐based reflection data is a problem of significant interest in seismic and ground‐penetrating radar (GPR) studies. A method to effectively address this problem has been recently presented, but our knowledge regarding the resolution of the corresponding inverse problem is still patchy. Here, we address this issue through an analytical approach based on the realistic assumption that the underlying velocity structure can be characterized as a scale‐invariant medium. We then test these analytical findings on pertinent depth‐migrated synthetic seismic images. In doing so, we also relax our original assumption that scale‐invariance prevails over the entire bandwidth of the source signal. The numerical results fully confirm our analytical findings, which indicate that the inversion of surface‐based seismic or GPR reflection data for the geostatistical properties of the imaged subsurface region is sensitive to the aspect ratio of the velocity heterogeneity and to the decay of its power spectrum, but not to the individual values of the horizontal and vertical correlation lengths.
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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) | 0.000 | 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