Application of Ground Penetrating RADAR for Profiling and Bathymetric Survey of Shallow Frozen
Bibliographic record
Abstract
Abstract Ground Penetrating Radar (GPR) was used to survey the bathymetry and sub-bottom features of a frozen lake in Ontario, Canada. A 50 MHz GPR measured the lake depth to a maximum of 24 meters. Sub-bottom features and sediment thickness were simultaneously observed and recorded with the GPR. Single beam sonar hydrographic surveying methods were applied to the data acquisition process and quality control procedures. Quality control checks revealed a vertical accuracy of approximately 0.25 meters while the horizontal positional accuracy was approximately 0.1 meters through the use of Real-time Kinematic (RTK) GPS. A contoured bathymetric map was generated from the data set as well as an isopach of sediment thickness. GPR is demonstrated to be effective for measuring water depth, ice thickness, and sub-bottom features of ice covered lakes.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".