GPS Tracking Performance under Avalanche Deposited Snow
Bibliographic record
Abstract
The tracking performance of several High Sensitivity Global Positioning System (HSGPS) receivers under avalanche deposited snow was investigated. Two field trials were held during April 2006 in the Canadian Rocky Mountains to study the factors affecting GPS signals and positioning performance. The PLAN Group at the University of Calgary has developed the miniature Global Navigation Asset Tracker (GNAT™) which integrates the SiRFstar IIe/LP or SiRFstar III GPS receivers with a microcontroller, onboard flash storage and a 2.4 GHz Zigbee modem. The test systems were placed entirely down a 6 cm borehole for 2.5 hours with position, velocity, time, status and raw observation data collected at 1 Hz. Post-mission analysis included determining GPS signal attenuation, pseudorange measurement error and availability along with single point position accuracy as they relate to the receivers depth in the snow pack. GPS Signal attenuation of approximately 1.8 dB per metre of snow penetration was measured. Methods of improving the position beneath the avalanche debris were investigated, resulting in horizontal position RMS values of 7.4 m and 2.8 m at snow depths of 2.0 and 2.68 m respectively.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".