Near-surface imaging in frozen environments using GPR
Bibliographic record
Abstract
This paper describes ground-penetrating radar (GPR) surveys that were conducted to characterize the ice and shallow subsurface of a frozen lagoon at Bowness Park, Calgary. We used Sensors and Software Inc.’s 250 MHz NOGGIN® and SmartCart® system as well as a Pulse EKKO 4 system with a 100 MHz antenna to acquire GPR surveys over the frozen lagoon in two consecutive years (2003 and 2004). Hyperbolic velocity analysis gave ice velocities of about 0.15 m/ns with velocities decreasing in the sediments to about 0.11 m/ns. We interpret the ice thickness to be about 0.4 meters from the GPR profiles, which is consistent with augur holes drilled through the ice. Channel sediments and stratigraphy beneath the ice are interpretable from the 3D radar reflectivity. We located and mapped a paleochannel with a NW-SE orientation and a thickness of about 0.5 meters. Penetration of the 250 MHz data reached about 2 meters at several locations in the area.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".