From the Tundra to Tierra del Fuego: Protecting Key Sites for Birds in Canada and throughout the Western Hemisphere
Bibliographic record
Abstract
Canada provides habitat for more than 470 species of migrating and non-migrating birds. They provide a number of ecosystem services; biological control, pollination, seed dispersal, seed germination and nutrient recycling. However their habitats are under increasing pressure from threats such as urban expansion, industrial agriculture, logging, mining and pollution. In order to ensure that our migrants return each spring, we must also work to conserve their vital habitat beyond our borders. Birds are important to conserve in their own right as they are an effective indicator taxon for environmental change; they are relatively large and diurnal, birds are close to ubiquitous geographically, are high on the food chain therefore reflecting change in a diversity of organisms and they are relatively long-lived so studies can be conducted over a number of years. Their distribution therefore helps us to identify areas where measures to conserve biodiversity are especially critical. Not all sites can be conserved so Important Bird Areas (IBAs) have been identified which are conservation priorities. Sites selected as IBAs are effective in capturing a high proportion of threatened, endemic and representative wildlife species other than birds.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".