Occurrence of swan hybrids around the Baltic Sea—an outcome of range expansions?
Bibliographic record
Abstract
Spectacular increases in range and numbers of some swan and goose species around the Baltic Sea have resulted in more contacts between species and facilitated mixed breeding. Records of mixed breeding and observations during the non-breeding season of mixed families, mixed pairs and hybrids in which at least one of the parent species was a swan were compiled for Sweden, Finland, Leningrad and Kaliningrad Regions of Russia, Estonia, Latvia, Lithuania, Poland, Germany and Denmark. There were twelve records of mixed breeding, nine of Mute Swan × Whooper Swan and one each of Mute Swan × Greylag Goose, Mute Swan × Greater Canada Goose and Whooper Swan × Bewick’s Swan. Excluding the two cases involving a goose and two cases involving swans with captive background, there were eight breeding records in the wild. Seven of these can be explained by range expansions. The exception was a case where the identification of the male was unsure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".