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Record W6892187879 · doi:10.5061/dryad.ht76hdrdq

Cryptic genetic diversity and cytonuclear discordance characterize contact among Canada jay (Perisoreus canadensis) morphotypes in western North America

2021· dataset· en· W6892187879 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNucleofectionTSG101HyporeflexiaTubulopathyProteogenomicsArticular cartilage damage

Abstract

fetched live from OpenAlex

Three distinct Canada jay (Perisoreus canadensis) morphotypes with easily recognizable plumage traits come into contact in western North America. Recent work demonstrated high genetic structure across the species’ range; however, patterns of genetic variation in these contact zones remain unknown. We categorized 605 individuals into one of three morphotypes (Pacific, Rocky Mountain, and Boreal) based on plumage, and genotyped individuals at the mtDNA control region and 12 microsatellite loci to assess the extent of hybridization between morphotypes. Our data showed cryptic genetic diversity and high cytonuclear discordance among morphotypes within contact zones, which is likely the result of recent and historical admixture. The distributions of the Boreal and Pacific morphotypes each showed a strong association with a single, distinct genetic group, whereas the Rocky Mountain morphotype exhibited higher genetic diversity and was associated with multiple genotypes. Our analyses show the importance of considering both plumage and genetic traits when examining contact zones between closely related taxa. Finally, the data presented in this study reaffirm that the Pacific morphotype is distinct from the Boreal and Rocky Mountain morphotypes based on genetic, phenotypic, and ecological data, indicating that the Pacific morphotype should be re-elevated to a full species.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.603
Threshold uncertainty score0.789

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.019
GPT teacher head0.230
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2021
Admission routes2
Has abstractyes

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