Tracking melt-freeze crust evolution in Val d'Aran (Catalan Pyrenees)
Bibliographic record
Abstract
ABSTRACT: In the Pyrenees, melt-freeze and wind crusts are a very common element in the snow cover. Such layers have an important role in both dry and wet slab avalanche trigger-ing. The crusts are characterized by a complex metamorphism and associated snow cover stability increase or decreases over time. To learn more about melt-freeze crusts, during 2013 late winter and early spring, we have been tracking different specific crusts in the Val d’Aran snowpack. The methodology is based on the following field observation: conducting stratigraphic profiles of the snow and other quantitative and qualitative measures of objective monitoring crusts. Quantitative variables are hardness (hand and penetration resistance), shear strength and density and qualitative description of the crust. Have also been con-ducted stability tests and were collected meteorogical data. The tracking was conducted out for 8 weeks, from February 27 to April 23, at three locations representative of the region of Val d'Aran in a north and south aspects. The objectives of the study are to evaluate the status of the crust as critical layers in the snowpack and the effectiveness of different stability test and compare the results obtained in Canada with the ones of the Pyrenees. The results show that in the tracking measurements in the crust, the density increases with time, the shear strength increases and hardness increase the over time decreases to degrade the crust. The crust indexes have a tendency to increase due to degradation of the layer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".