Bibliographic record
Abstract
Between 80 000 and 150 000 marine birds wintering in the Bay of Biscay were killed during the “Erika” oil spill. Three complementary studies were conducted to investigate the geographic origins of these birds. The common guillemot, Uria aalge, represented more than 80% of the oiled birds and these studies thus focused primarily on this species. Analyses of 184 ring recoveries and biometry of 1851 corpses indicated that guillemots originated from a large geographic area, including colonies from across the British Isles and the North Sea, along with more northern localities. However, the majority of individuals came from colonies located between western Scotland and the Celtic Sea. The third study, based on a population genetic approach using microsatellite markers (samples from dead oiled birds and from more than 600 birds caught in 19 breeding colonies), showed little genetic differentiation among north-eastern Atlantic guillemot colonies. This result limits the ability to identify the geographic origins of the birds using only DNA samples, but reveals a significant amount of gene flow among colonies. Overall, results indicate the large spatial scale of the oil spill's impact and underline the usefulness of combining multiple approaches to assess the local and regional effects of such accidents.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".