Just Add Water and Stir: An Artificial Suburban Lake Develops Into an Important Moulting Site for Large‐Bodied Herbivorous Wildfowl
Bibliographic record
Abstract
ABSTRACT Egø Engsø is an artificial Danish suburban lake created in 2006, primarily for nutrient retention and flood control. Expanding submerged macrophyte cover (dominated by Stoneworts Chara spp. and Pondweeds Potamogeton spp.) attracted moulting concentrations of 600 mute swans Cygnus olor, 1100 greylag geese Anser anser and 280 Canada geese Branta canadensis. These unexpected additions to the avifauna benefit from reliable food supplies and effective protection from recreational disturbance on and near the water surface. Egø Engsø is a model of enabling intense human activity at a waterbird moulting site, and confirming appropriate planning can accommodate multiple functional objectives following wetland creation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".