Retrieving dry snow stratigraphy using a versatile low-cost frequency modulated continuous wave (FMCW) K-band radar
Why this work is in the frame
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Bibliographic record
Abstract
Considering the increased popularity for backcountry mountain recreation activities, potentially problematic snowpack interfaces are currently of great interest given their impact on snow stability. The identification of interface vertical locations and spatial variability in the snowpack is essential for avalanche danger forecasting. The Gaspé Peninsula specific climate often leads to a complex snowpack development, where the need of improved monitoring is important. The goal of this research is to assess an automated method to detect contrasted snow interfaces using a 24 GHz Frequency Modulated Continuous Wave (FMCW) portable radar. Based on different in-situ configurations, we compared the radar amplitude signals with in-situ snow geophysical measurements, including SnowMicroPenetrometer (SMP). Radar measurements have been done following two different protocols: (1) mobile radar looking-up and down in order to understand the radar-snow wave interactions and optimize its parameters for spatial variability assessment of contrasted snow layers and (2) fixed radar looking-up to evaluate its potential in monitoring snow stratigraphy temporal variability. Results show good agreements with compared validation data with 80% of manually identified interfaces detection and a vertical positioning error of 3 cm. The presented FMCW radar appears to have a good potential for spatial and temporal variability assessment of snowpack stratigraphy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it