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Hybridization and changes in the distribution of Iceland gulls (<i>Larus glaucoides/kumlieni/thayeri</i>

2000· article· en· W2161987043 on OpenAlexaboutno aff
Douglas N. Weir, Andrew C. Kitchener, R Y McGowan

Bibliographic record

VenueJournal of Zoology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyLarusZoologyDistribution (mathematics)FisheryEcologyFish <Actinopterygii>Herring

Abstract

fetched live from OpenAlex

Abstract Three Iceland gull taxa were defined mainly from adult wingtip melanism. Up until about 1860, nominate glaucoides (no melanism) was known to breed from Greenland to western High Arctic Canada, but by about 1900 it was essentially confined to Greenland. Until 1860, thayeri (most melanism) was known only from western High Arctic Canada, but from 1900 to 1980 it was found throughout High Arctic Canada and in a small part of north‐west Greenland. At high latitudes in Canada it replaced glaucoides , with which it was formerly sympatric in the west and probably interbred. The first known kumlieni (intermediate, variable melanism) were from west Greenland in the 1840s, and by 1900 the western and northern limits of most of its breeding range in the eastern Canadian Low/High Arctic were known. The range of kumlieni lies between those of thayeri and glaucoides and overlaps both; kumlieni bred in Greenland by 1964. It freely interbreeds with thayeri and probably with glaucoides . Winter ranges of glaucoides and thayeri have changed little since they were first determined for glaucoides by 1860 and for thayeri by the 1920s. However, winter adult kumlieni was unknown from Greenland to the British Isles until 1900; there were a few records prior to 1915 and progressively more after 1950. The study adds to the evidence that kumlieni represents introgressive hybridization by western thayeri into eastern glaucoides . D. N. Weir died 15 August 2000.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.243
Threshold uncertainty score0.148

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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 teacher head, 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

Citations9
Published2000
Admission routes1
Has abstractyes

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