Civilian Helicopter Accidents into Water: Analysis of 46 Cases, 1979-2006
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: When a helicopter crashes or ditches into water the crew and passengers must often make an escape from underwater and a number of the occupants do not survive. This paper examined fatality rates, human factors problems with escape, and causes of death in Canadian civilian registered helicopter accidents in water (1979-2006). METHOD: Data obtained from the Transportation Safety Board of Canada was reviewed. Key issues such as fatalities, injuries, warning time, sinking, and inversion were examined. RESULTS: There were 46 helicopters that ditched into water. There were 124 crew and passengers involved. Of those, 27 (23%) crew and passengers died. Lack of warning time (55%), rapid sinking (72%), and inversion (35%) were the most common issues in the accidents. CONCLUSION: Survival rates for Canadian registered helicopter accidents into water (78%) show little change from previously reported worldwide data. Lack of warning time, rapid sinking, and inversion were the significant factors in the survival rate. The practical implication is that crew and passengers involved in planned flights over water must wear all the life support equipment on strap-in and not have it stowed on the back of the seat or in the cabin.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it