Northward migration of Red Knots <i>Calidris canutus rufa</i> and environment connectivity of southern Brazil to Canada
Bibliographic record
Abstract
Summary During their northward migration, Red Knots Calidris canutus rufa stop at the Lagoa do Peixe National Park in the extreme south of Brazil to build up fat reserves for their journey to their Canadian breeding grounds. We tracked five Red Knots with PinPoint Argos-75 GPS transmitters to investigate differences in migration strategies from this stopover. Tracked birds used two different routes: the Central Brazil route and the Brazilian Atlantic Coast route. One bird flew 8,300 km straight from Lagoa do Peixe to the Delaware Bay (USA). Another bird stopped in Maranhão (north-east Brazil) and a third one used a yet unknown environment for the species, the mouth of the Amazon River at Baía Santa Rosa, Brazil. These two birds made short flights, covering stretches of 1,600 km to 3,600 km between stop-overs, where they stayed from 4 to 18 days. Our study highlights the occurrence of intrapopulation variation in migratory strategies and reveals the connectivity of environments that are essential for the viability of rufa Red Knot populations.
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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".