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Record W7052027616

Predation by Great Black-backed Gulls on Banded Waterfowl

2024· article· en· W7052027616 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101DysgeusiaDiafiltrationLiquationEmperipolesisTriacetinDurvalumab
DOInot available

Abstract

fetched live from OpenAlex

During the winter waterfowl banding seasons in 1980, 1982, 1983, 1985, and 1986 on Seneca Lake in central New York State, two Great Black-backed Gulls (Lares marinus) have attacked and killed newly banded and released waterfowl.Their predatory behavior is systematic and largely unvarying.The Great Black-backed Gull has extended its winter range in the last few decades to include the eastern Great Lakes where their numbers have been steadily increasing (Peakall 1967, Bull 1974).During this period, a small number of individuals has regularly appeared during the winter at the northern end of Seneca Lake, one of the large Finger Lakes in central New York State, 46 km south of Lake Ontario (Peakall 1967).The Great Black-backed Gull has been described by Audubon as "...the tyrant of sea-fowl...", and by Nuttall as "...a particular enemy of the graceful eider, pouncing upon and devouring its young on every occasion, and often kills considerablesized ducks" (Nuttall 1834: 309).Studies of the food habits of the Great Black-backed Gull have been done by Harris (1965) on islands off the coast of Wales, Hunt and Hunt (1973) in Maine and Northwestern Europe, Threlfall (1968) in Newfoundland, Koch (1974) in Helgoland in the North Sea, and Ingolfsson (1976) in Iceland.They clearly demonstrated that this species is a generalized forager, an opportunistic omnivore like other large gulls, but a greater scavenger and predator.Several observers have published accounts of Great Blackbacked Gulls attacking and killing adult birds including waterfowl (Kuerzi 1937, Addy 1945, Gross 1945, Cobb 1957, Mansueti 1961, Presnal11968, Andersson and Fridzen 1970, Svensson 1971, Halliday 1977); other Great Black-backed Gulls (Corkhill 1971); migrating passetines (MacDonald and Mason 1973); Atlantic Puffins (Fratercula arcrice) and Manx Shearwaters (Puffinuspuffinus) (Robinson 1930, Harris 1965); and a Horned Grebe (Podiceps auritus) (Waltevens 1985).METHODS Everywinter for over thirtyyears I have operated a waterfowl banding station during the months of January, February and March at Kashong Bay on the west shore of Seneca Lake, 11 km south of the city of Geneva which is at the northern.end

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.193
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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