High-resolution images of shallow aquifers—A challenge in near-surface seismology
Bibliographic record
Abstract
Abstract A near-surface multifold high-resolution seismic reflection experiment was conducted in the vicinity of the waste management area of a potash mine in western Canada. A buried channel was identified in the data, and the stratigraphy of the Quaternary infill of this structure was mapped. The spatial extent of several prominent gravel-sandy aquifers, which represent the hydrogeologic framework of the region, was outlined by the survey. The seismic signatures also established the hydraulic independence of three major aquifers along the survey line. The complex heterogeneous lithology of the surface cover limited effective elastic-wave generation to surface sources. This geologic framework also caused propagation of strong diverse coherent-noise patterns which severely degraded reflected signal. The suppression of those overhelming interfering events required the design of noise-specific filters and their sequential multistep implementations. Results of forward modeling of background geologic information were crucial factors in the design of the data acquisition program and preliminary choices of the processing parameters, and (along with borehole data) were the primary guidance in the geologic interpretation of the final seismic section. Fundamental procedures were developed for mapping of glacial tills in the Western Canadian Basin, techniques that can be applied in other regions with similar near-surface glacial stratigraphy. The experiment revealed that even closely spaced borehole information could never duplicate the detail of the subsurface images of the seismic data.
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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 | 0.000 | 0.001 |
| 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 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".