Bibliographic record
Abstract
Goose roundup called inhumane. During the early summer, goose problems affect cities across the United States. Summer is also the time to round up many of these geese for relocation or for euthanization. In Oregon, nuisance Canada geese are being used to feed the hungry. A similar goose‑removal project was carried out at Saddle River County Park, New Jersey. National Park Service spares geese around JFK airport. Federal and local agencies have requested that the NPS reduce the goose population in the Gateway National Recreation Area. Looking for wildlife at the Great Falls, Montana, airport. Similar to many airports across the country, the airport at Great Falls, Montana, is working on its wildlife hazard plan, which is mandated by the Federal Aviation Administration, to reduce wildlife-aircraft strikes. White-nose syndrome continues to spread among bats. The disease has now spread southward from near Albany, New York, through much of the Appalachian Mountains and westward into Missouri. Wildlife managers recommend a high level of biosecurity for those who routinely work with bats. Mountain lion sighting confirmed by a state official in central Indiana. The determination was made from photographs taken by a motion‑sensitive game camera.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.281 | 0.185 |
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".