Buried‐Channel Imaging Using P‐ and SH‐Wave Shallow Seismic Reflection Techniques, Examples from Manitoba, Canada
Bibliographic record
Abstract
Buried channels are erosive sedimentary features that can possibly be formed by sub-glacial melt-water circulation. The size of these channels is very variable with widths up to several kilometers and depths from few meters up to several hundreds of meters. Their coarse-gravely, sandy sediment fills act as reservoirs which can be important sources of water or occasionally gas. In the fall of 2006, comparative seismic reflection tests were conducted in south-western Manitoba over a buried channel aquifers that is capped by glacial till. Tests included an in-hole shotgun source with planted geophones, landstreamers with vibroseis technology (Minivib) in P-wave and SH-wave mode and an impulsive sledge-hammer source. The highest quality results were obtained using a Minivib. Uncorrelated data recording has allowed major signal spectral improvements. The best resolution and signal/noise ratio have been obtained using a SH vibroseis signal with a 48 channel landstreamer (a geophone spacing at 0.75 m and shot-spacing at 1.5 m) and the fastest acquisition is realized using a P-wave landstreamer. A rate of 2-D profiling of up to 2.2 km/day has been achieved using a SH-landstreamer and up to 3 km/day using a P-wave landstreamer.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".