Bibliographic record
Abstract
We present a case report of a helicopter pilot who fell into a crevasse during a fuel delivery in Antarctica. He was trapped alone in the crevasse for 3 h while waiting for a rescue team to arrive, and a further 1 h during the extrication process. His condition deteriorated during the extrication and he lost consciousness and signs of life minutes after being dragged over the lip of the crevasse. He was then loaded into the rescue helicopter and treated with intermittent cardiopulmonary resuscitation during the 39-min return flight. Initial esophageal temperature on arrival at the Davis Base medical facility was 24.2°C. After 18 h of further treatment (mechanical ventilation with warm humidified O2, with internal and external warming) he was pronounced dead. The cause of death was hypothermia with minimal physical injury. This case highlights some of the extra challenges facing operational, rescue, and medical personnel in an isolated location. These complications include the tendency for flight crew to remove cold weather clothing during flight due to restricted mobility and excessive heat load from cabin heating; extended time for arrival of the rescue crew; extrication in a confined space; limited helicopter cabin space for transporting the rescue team and their rescue and medical equipment; and extended transport time to the nearest medical facility.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".