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Record W3160409913 · doi:10.34080/os.v21.22609

Occurrence of swan hybrids around the Baltic Sea—an outcome of range expansions?

2011· article· en· W3160409913 on OpenAlexaboutno aff
Hakon Kampe-Persson, Dmitrijs Boiko

Bibliographic record

VenueOrnis Svecica · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersEuropean Social FundState Education Development Agency Republic of Latvia
KeywordsGooseRange (aeronautics)GeographyHybridSeasonal breederBaltic seaFisheryZoologyEcologyBiologyOceanography

Abstract

fetched live from OpenAlex

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.

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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.280
Teacher spread0.220 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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