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Record W6894262313 · doi:10.5683/sp2/b57jl1

Data from: Multiple reproductive barriers separate recently diverged sunflower ecotypes

2021· dataset· en· W6894262313 on OpenAlexaff

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReproductive isolationGenetic algorithmGene flowEcotypeEcological speciationSelection (genetic algorithm)Incipient speciationAssortative mating

Abstract

fetched live from OpenAlex

AbstractMeasuring reproductive barriers between groups of organisms is an effective way to determine the traits and mechanisms that impede gene flow. However, to understand the ecological and evolutionary factors that drive speciation, it is important to distinguish between the barriers that arise early in the speciation process and those that arise after speciation is largely complete. In this paper we comprehensively test for reproductive isolation between recently diverged (< 10,000 years bp) dune and non-dune ecotypes of the prairie sunflower, Helianthus petiolaris. We find reproductive barriers acting at multiple stages of hybridization, including premating, postmating-prezygotic, and postzygotic barriers, despite the recent divergence. Barriers include extrinsic selection against immigrants and hybrids, a shift in pollinator assemblage, and post-pollination assortative mating. Together these data suggest that multiple barriers can be important for reducing gene flow in the earliest stages of speciation.

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)0.001
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.016

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 head0.053
GPT teacher head0.309
Teacher spread0.256 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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