Migration chronology of Eastern-Population Tundra Swans
Bibliographic record
Abstract
We used satellite platform transmitting transmitters (PTTs) in 19982000 to track spring and fall migratory movements of Tundra Swans (Cygnus columbianus columbianus) captured at Long Point, Ontario. Migration corridors reported here corroborated those identified in previous studies using alphanumerically coded neck collars. However, PTTs provided additional information on duration of spring and fall migrations, duration of stay in different staging regions, time spent on breeding and wintering areas, and migration speed. Birds migrated between the Atlantic coast and northern prairies along a narrow geographic corridor through portions of the southern Great Lakes. From the northern prairies, swans followed 3 corridors to breeding areas on the west coast of Hudson Bay, central High Arctic, and Mackenzie River delta. While swans spent considerable time on Great Lakes (27% of spring migration) and northern prairie (40%) staging areas in spring, the northern boreal forest was an important fall staging area (48% of fall migration). Tundra Swans spent 20% of the annual cycle on wintering areas, 28% on spring staging areas, 29% on breeding areas, and 23% on fall staging areas. The long duration of migration and the fact that birds spend half their lives on staging areas underscore the importance of conserving Tundra Swan migratory habitats. Thirty-gram neck-collar-attached PTTs were more suitable than 95-g Teflon-harness-attached backpack PTTs for tracking Tundra Swans.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".