Wilderness Mass Casualty Incident (MCI): Rescue Chain After Avalanche at Everest Base Camp (EBC) In 2015
Bibliographic record
Abstract
The Nepal Earthquake of 2015 killed over 8000 people and injured over 20,000 in Nepal. Moments after the earthquake, an avalanche of falling ice came down from above Everest Base Camp (EBC). The air blast created by the avalanche flattened the middle part of EBC, killing 15 people and injuring at least 70. The casualties were initially triaged and treated at EBC and then evacuated by air to Kathmandu for definitive care. There were intermediate stops at the villages of Pheriche and Lukla during which the casualties were offloaded, retriaged, treated, and loaded again for further transport. Most of the authors of this article helped to provide primary disaster relief at EBC, Pheriche, or Lukla immediately after the earthquake. We describe the process by which an ad hoc rescue chain evacuated the casualties. We discuss challenges, both medical and nonmedical, what went well, and lessons learned. We make recommendations for disaster planning in the Khumbu (Everest) region, an isolated high altitude roadless area of Nepal.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".