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Record W6931768977 · doi:10.5683/sp3/udd4cd

Introgression between Sphyrapicus nuchalis and S. varius sapsuckers in a hybrid zone in west-central Alberta

2022· dataset· en· W6931768977 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2022
Typedataset
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsRoyal Alberta MuseumUniversity of LethbridgeUniversity of British Columbia
Fundersnot available
KeywordsIntrogressionHybrid zoneHybridBackcrossingPlumageReproductive isolation

Abstract

fetched live from OpenAlex

Abstract Studying species interactions at hybrid zones allows biologists to understand the forces that promote speciation. Hybridization among Sphyrapicus nuchalis, S. varius, and S. ruber has long been acknowledged, and hybrid zones between S. nuchalis/S. ruber and S. varius/S. ruber have been characterized with both genetic and genomic data. Using a combination of next-generation Restriction Site-Associated DNA sequencing (RAD-Seq) and traditional genetic methods, we examined patterns of introgression in the poorly characterized S. nuchalis/S. varius contact zone; the two most similar species in the complex, though they are not each other’s closest relatives. We found high introgression rates, with several early and many advanced generation hybrids along a 275 km stretch of Rocky Mountain foothill, pointing to a well-established hybrid zone with hybrid individuals backcrossing with individuals from the parental species and each other. Plumage colouration in the hybrid zone was a relatively poor indicator of parental or hybrid status, which could be attributed to the possible involvement of few large effect genes.

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)0.000
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: Dataset · Consensus signal: none
Teacher disagreement score0.122
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.027
GPT teacher head0.379
Teacher spread0.352 · 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
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

Citations0
Published2022
Admission routes2
Has abstractyes

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