Migratory Canada geese cause crash of US Airways Flight 1549
Bibliographic record
Abstract
In the United States alone, over 7400 bird–aircraft collisions (birdstrikes) were reported in 2007. Most of these strikes occurred during takeoff or landing of the flight, and it is during these flight phases that aircraft experience their highest risk of substantial damage after colliding with birds. Birdstrikes carry enormous potential costs in terms of lives and money. Using feather remains and other tissue samples collected from the engines of US Airways Flight 1549, which crash landed in the Hudson River in New York City on 15 January 2009 after a birdstrike, we apply molecular tools and stable hydrogen isotopes to demonstrate that migratory Canada geese were responsible for the crash. Determining whether the geese involved in this birdstrike event were resident or migratory is essential to the development of management techniques that could reduce the risk of future collisions. Currently, the US civil aviation industry is not required to report birdstrikes, yet information on frequency, timing, and species involved, as well as the geographic origin of the birds, is critical to reducing the number of birdstrikes. Integrating this information with bird migration patterns, bird‐detecting radar, and bird dispersal programs at airports can minimize the risk of such collisions in the future.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".