Bibliographic record
Abstract
ABSTRACT Surface hoar crystals are common on the surface of mountain snow covers. Once buried, layers of large plate-shaped surface hoar crystals are prone to releasing dangerous snow-slab avalanches. Since snow microstructure influences the optical properties of snow, remote sensors could potentially detect the formation of surface hoar and other snow types associated with avalanche release. The spectral reflectance of 377 snow samples was measured with a field spectrometer between 750 and 2500 nm, including 161 samples of surface hoar. Morphological snow shapes associated with critical avalanche layers (surface hoar, near-surface faceted particles and depth hoar) had lower average reflectance factors than non-critical snow shapes at infrared wavelengths. Needle-shaped surface hoar was more reflective than plate-shaped surface hoar, but there were no significant differences between different sizes of surface hoar. Normalized difference indices calculated with reflectance from two wavelength bands is presented as a potential method to classify critical snow surfaces remotely, although melt-freeze crusts near the surface complicated the classification. Accordingly, further studying on the effect of melt-freeze crusts and quantification of the bidirectional reflective properties of critical snow types is needed.
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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 | 0.001 | 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".