Snow cornice and snow avalanche monitoring using automatic time lapse cameras in Tasiapik Valley, Nunavik (Québec) during the winter of 2017–2018
Bibliographic record
Abstract
A series of automatic time-lapse cameras installed along the southwestern side of Tasiapik Valley, near the village of Umiujaq, Nunavik (northern Québec) documented several departure modes and types of snow involved in snow avalanches during winter 2017–2018. These included cornice–avalanche dynamics, slab and loose snow avalanches, and clean and dirty snow avalanches. At the top of the selected slope, a camera monitored the development of a snow cornice beginning in November 2017, detecting multiple cornice failures over the winter and spring. The track and deposition area of the runout paths were monitored from two cameras downslope, revealing the concomitance of snow–cornice fall and snow avalanche triggering. Snow avalanche activity remained relatively infrequent until the end of May 2018. Spring snow avalanche activity is characterized by wet and dirty snow avalanches carrying debris to the foot of the slope and by runout zones located near the road along the slope.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".