Blade Hardness Gauge: Snow Hardness Measuring and Analysis Techniques
Bibliographic record
Abstract
Abstract. The blade hardness gauge (BHG) is a promising technology for avalanche forecasters, technicians, and researchers. Designed and produced by Fraser Instruments Ltd., the BHG resembles and is based on the thin-blade tool introduced by Borstad and McClung in 2011. The BHG was designed to quantitatively measure snow hardness without the known biases of the hand hardness test. Research was carried out in the Canadian mountains of British Columbia and Alberta during the 2020–21 and 2021–22 winter seasons to test the reliability and integrity of the BHG. Side by side snow hardness profile comparison amongst avalanche practitioners shows that the BHG is more consistent for measuring snow hardness than the hand hardness test. A blade hardness to hand hardness comparative scale was developed to utilize the BHG as a teaching tool for the hand hardness test. This paper proposes refinements to standard data collection methods and techniques including the insertion rate and orientation of the thin-blade into the snowpack. These recommendations aim to increase consistency amongst users and highlight applications for avalanche practitioners to use in the field.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".