Safety Considerations for Medical Staff and Patients Who Fly Over Water in a Helicopter for Work or Recreation
Bibliographic record
Abstract
BACKGROUND: Around 25% of people involved in a helicopter accident in water do not survive. From time to time, physicians and their medical staff are required to fly over water in a helicopter to attend one or more seriously ill patients. Many will have had little or no experience of the issues involved if the helicopter has an accident in the water. Also as Family Practitioners, Aeromedical Examiners, and Flight Surgeons, they are asked to provide advice to patients, travel agents, and airline booking agents about whether an overwater helicopter flight is advisable or not. METHOD: From 50 yr of helicopter accident evidence in the scientific literature, government agency reports, and statistics from the military safety centers and the offshore oil industry, the critical hazards involved and risks to medical staff and their patients have been identified. RESULTS: Patients most at risk are those who suffer from cardiovascular or respiratory disease, have physical disabilities, have a very large body size, and anyone who is a non-swimmer. Medical staff are at risk if they are not familiar with the procedure for escape from a flooded inverted cabin and difficulties after escape from the fuselage with life jackets, life rafts, and sometimes the necessity to swim ashore. CONCLUSIONS: With 50 yr of hindsight, many of the deaths were preventable, and many lives can be saved if a series of very simple mental and physical preventive actions are taken by anyone stepping on to a helicopter that flies over water.Brooks CJ, MacDonald CV. Safety considerations for medical staff and patients who fly over water in a helicopter for work or recreation. Aerosp Med Hum Perform. 2017; 88(4):413-417.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".