<title>Corrected GPR velocity and attenuation tomography of artifacts due to media anisotropy, borehole trajectory error, and instrumental drifts</title>
Bibliographic record
Abstract
Using standard inversion algorithm, velocity and attenuation tomograms can show artifacts which compromise interpretation. These artifacts can be due to errors in borehole trajectory measurements, medium anisotropy, T0 (initial time) or A0 (initial amplitude) drifts. In order to cancel these artifacts, the error sources can be introduced as unknown parameters in inversion algorithms (Hollender, 1999). In this paper, we present results obtained with crosshole radar data, recorded in a limestone quarry. Using the appropriate algorithms, all the artifacts have been cancelled and tomograms show clearly subhorizontal structures in agreement with the quarry stratification. In our data set, results do not reveal significant trajectory error, and T0 and A0 drifts are low. However, the presence of a velocity and attenuation anisotropy appears clearly on the tomograms. In the case of attenuation tomograms, the high anisotropy rates could be explained by the cumulative effect of the partitioning of energy due to reflection and transmission mechanisms at interfaces, and medium anisotropy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.029 | 0.010 |
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".