COMPETITION IN THE AIR: BIRDS VERSUS AIRCRAFT
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
THE FIRST KNOWN aircraft fatality that was directly attributable to a bird occurred in 1912, when a gull (Larus sp.) was caught in the control cables of an aircraft, causing it to crash.Since that time, aircraft have generally increased in size to carry more passengers.Birdaircraft conflicts are becoming more common recently, which is possibly due to increased numbers of both aircraft (e.g. an estimated 28 million jets now take off in the United States as compared to 18 million in 1980) and some kinds of bird species (e.g.Canada Geese [Branta canadensis], in the United States have quadrupled to 2 million since 1985).Between 1990 and 1998, there were an estimated 22,000 bird-aircraft collisions in the United States, which cost an annual $400 million in aircraft repairs.This bird-aircraft conflict takes place around the world, although the species, situations, and severity differ.It is estimated that at least 350 people have been killed in bird-aircraft collisions worldwide.Understanding bird-aircraft conflict is critical due to monetary reasons and the potential threat to human life.Despite the severity of the situation, bird-aircraft conflict has largely remained on the fringes of rigorous ornithological investigations, and sound ornithological understanding is still required to find longterm management solutions for that conflict.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it