Combined Migration of GPR data for layered media
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Bibliographic record
Abstract
<p>In this contribution we will propose the combination of migration results achieved from the same GPR dataset, aimed to mitigate the effects of the nonuniformity of the propagation velocity of the waves throughout the investigated domain. The nonuniformity of the propagation velocity can be appreciated from the diffraction hyperbolas [1] possibly present in the data, or directly from the results of the focusing [2] achieved from different trial values of the propagation velocity. In ref. [3] an algebraic combination of two (but theoretically even more) migration results achieved from different migration parameters applied to the same data has been shown. In that paper, the case of a horizontal variation and the case of a vertical variation of the propagation velocity of the electromagnetic waves in the soil were considered. Here, we will consider the case of a layered medium with non-flat interface between two adjacent layers, which is a case of interest in several practical application, and is a case where we have both a vertical and a horizontal variation of the parameters. Analogously to ref. [3], we will consider both the aspect of the focusing and that of the combined time-depth conversion.</p><p> </p><p><strong>References</strong></p><p><strong> </strong></p><p>[1] R. Persico G. Leucci, L. Matera, L. De Giorgi, F. Soldovieri, A. Cataldo, G. Cannazza, E. De Benedetto, Effect of the height of the observation line on the diffraction curve in GPR prospecting, Near Surface Geophysics, Vol. 13, n. 3, pp. 243-252, 2015.</p><p>[2]G. Gennarelli, I. Catapano, F. Soldovieri, R. Persico, On the Achievable Imaging Performance in Full 3-D Linear Inverse Scattering, IEEE Trans. on Antennas and Propagation,  vol. 63, n. 3, pp. 1150-1155, March 2015.</p><p>[3] R. Persico, G. Morelli, Combined Migrations and Time-Depth Conversions in GPR Prospecting: Application to Reinforced Concrete, Remote Sens. 2020, Volume 12, Issue 17, 2778, open access, DOI 10.3390/rs12172778</p><p> </p><div><br><div> <p> </p> </div> </div>
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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