Introduction to Special Topic Birds and Aircraft—Fighting for Airspace in Ever More Crowded Skies
Bibliographic record
Abstract
This special issue of Human-Wildlife Conflicts (HWC) was conceived 1 year ago by Bird Strike Committee-USA (BSC-USA) and the Berryman Institute.Our premise was that the collision of aircraft with birds (bird strikes) and other wildlife is a growing problem about which the general public and most scientists and wildlife biologist know very little.Furthermore, although considerable work has been done to mitigate the risks caused by bird strikes, there have been few peer-reviewed publications of these research and management efforts.Thus, our 2 goals were to ( 1) educate the broad readership of HWC about the growing safety and economic problems caused by bird strikes, and (2) provide an outlet for peer-reviewed research and commentary on methods to mitigate these risks.Most of the papers published in this edition are based on technical presentations delivered at the joint meeting of BSC-USA and BSC-Canada hosted by Orlando-Sanford International Airport, Florida, in August 2008 ( ).In the aftermath of the miraculous ditching of US Airways Flight 1549 in the Hudson River on January 15, 2009, in which 155 passengers and crew were safely evacuated, the goal of education about bird strikes has been achieved.Although those of us working on this problem were aware that at least 210 aircraft have been destroyed by bird strikes and other wildlife strikes in the past 20 years (Richardson and West 2000;Thorpe 2003Thorpe , 2005; Dolbeer, unpublished data), this single, highly-publicized event dramatically demonstrated to the world at large that birds can bring down large transport aircraft.Based on the analysis of bird-remains recovered from the downed aircraft, the National Transportation Safety Board (NTSB) released interim findings on February 12, 2009(NTSB 2009).The report stated that at least 1 Canada goose (Branta canadensis) had been
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.163 | 0.055 |
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".