Was an Avalanche Swarm Responsible for the Devastation at Mount Everest Base Camp During the April 2015 Nepal Earthquake?
Bibliographic record
Abstract
Moore, G.W.K., Paolo Cristofanelli, Paolo Bonasoni, Gian Pietro Verza, and J.L. Semple. Was an avalanche swarm responsible for the devastation at Mount Everest Base Camp during the April 2015 Nepal earthquake? High Alt Med Biol . 21:352–359, 2020. Introduction: An avalanche triggered by an earthquake on April 25, 2015, struck the Mount Everest Base Camp (EBC) resulting in 15 deaths and over 70 injuries. Despite the common occurrence of avalanches in this region, little is known about their intensity and the stability of the glaciers that ring the Mount Everest massif. Here we present unique observations from a nearby automatic weather station (AWS) in the minutes just after the earthquake. Methods: Several (AWS) were deployed along the Khumbu Valley in Nepal. The site at Kala Patthar (elevation 5,613 m asl) 3.5 km from EBC and 4 km from the col along the ridge between Pumori and Lingtren was active from 2010 to 2015 and recorded temperature, relative humidity, pressure, solar radiation, and wind speed and direction. Results: The sequence of wind direction anomalies indicated that multiple air blasts passed the AWS, each associated with a distinct avalanche source, suggesting that earthquake likely caused a number of distinct avalanches from different source regions along this ridge. Discussion: Results suggest that a swarm of avalanches collectively lead to the death and destruction at EBC, suggesting the need for improvement in our understanding of avalanches in the region as well as in our ability to model and forecast such events.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".