Bibliographic record
Abstract
In counts of gulls, terns, wildfowl and waders breeding on about 100 small islands along the mainland coast of west Scotland during 1996–2009, 123 clutches containing the eggs of two species (‘mixed clutches’) were found among 69,775 clutches of 20 species (0.18%). The annual percentage varied between 0.09% and 0.33%. Most (89%) mixed clutches contained only one egg of one of the species. The 123 mixed clutches involved 13 species, 19 species-pairs and at least 31 permutations of guest and host species. The most frequent species-pairs were Common Gull Larus canus and Eurasian Oystercatcher Haematopus ostralegus, Herring Gull Larus argentatus and Common Eider Somateria mollissima, and Common Gull and Black-headed Gull Larus ridibundus, these together accounting for 54% of cases. Sixteen species-pairs had been recorded in an earlier study in 1990–95, and a further six were found in 1996–2009: Common Eider and Mallard Anas platyrhynchos (4 mixed clutches), Herring Gull and Great Black-backed Gull Larus marinus (3), Common Tern Sterna hirundo and Arctic Tern Sterna paradisaea (2), Canada Goose Branta canadensis and Common Eider (2), Common Eider and Greylag Goose Anser anser (1), and Canada Goose and Greylag Goose (1). The appearance of goose eggs in mixed clutches reflected large increases in breeding numbers of both species in the area. The most frequent guest species were Eurasian Oystercatcher and Common Eider and the most frequent hosts were Common Gull and Herring Gull. Mixed clutches probably arise from attempted egg parasitism. There are records of chicks from guest eggs being reared successfully in some closely related species-pairs, but other species-pairs seem incompatible.
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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 | 0.000 | 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) | 0.002 | 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".