Bibliographic record
Abstract
Mute swans (Cygnus olor) are an invasive species originally brought to the United States in the late 19th and early 20th centuries for ornamental ponds and lakes, zoos and aviculture collections. Original populations were located in northeastern states along the Hudson Valley but have since expanded to several Midwestern states and portions of the western U.S. and Canada. Mute swan damage includes competing with native waterfowl, destroying native plants, spreading disease, and colliding with aircraft. They are also considered a nuisance in some areas due to their abundant fecal droppings and aggressiveness towards people. Mute swans can impact ecosystems by foraging on native plants and competing with native species for food and habitat. Mute swans forage primarily on submerged aquatic vegetation, and each swan consumes 4 to 8 pounds of vegetation per day. While feeding, mute swans use their feet to expose plant shoots and roots for foraging, and to help dislodge food for cygnets (i.e., young swans). This damages aquatic substrates and vegetation surrounding preferred foods. Mute swans typically consume less than 50 percent of what they remove. Results from one study showed their diet overlaps considerably with many native waterfowl species that overwinter in the lower Great Lakes or temporarily use the area during migration. Mute swans are known for their highly territorial behavior during their breeding season, and may compete with native wildlife for space and associated resources. Of particular concern are potential impacts on threatened and endangered species. During the breeding season, mute swans sometimes displace other native waterfowl from preferred nesting locations, and may kill adult and juvenile ducks and geese. During one incident in Maryland, a large molting flock of mute swans caused a colony of least terns (Sterna antillarum) and black skimmers (Rynchops niger) to abandon a nesting colony by trampling nests, eggs, and chicks. The mute swans also displaced nesting common terns (Sterna hirundo). In 2011 in Michigan, a mute swan nest was found in the middle of a black tern (Chlidonias niger) colony that had previously supported approximately 54 black terns in 2009. Only a few black tern nests remained, approximately 30 to 40 feet away from the swan nest.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".