Bibliographic record
Abstract
The bald eagle (Haliaeetus leucocephalus) population in the United States has made a tremendous recovery from fewer than 500 nesting pairs in 1970, to over 10,000 pairs in 2007. It is likely that the population will continue to grow. Every state, except Hawaii, now has nesting bald eagles. Because of the widespread recovery, the U. S. Department of the Interior removed the bald eagle from the Endangered Species List in August 2007. Bald eagles are still protected by the Migratory Bird Treaty Act and the Bald and Golden Eagle Protection Act as well as by state laws. At airports across the United States of America biologists are finding it difficult to manage bald eagles that threaten aviation safety. This difficulty arises because of the restrictive laws which protect this species, and the intense public interest and concern for eagles. As the eagle population continues to grow, so do the number of eagle strikes with aircraft. Overall, there were 84 reported civil aircraft strikes with bald eagles in 18 U.S. states and one in Canada to a U.S. carrier from 1990-2006. The mean number of strikes/year has increased 7-fold in the lower 48 states since 1990.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".