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Record W2996602786 · doi:10.3390/genes10121040

Skim-Sequencing Reveals the Likely Origin of the Enigmatic Endangered Sunflower Helianthus schweinitzii

2019· article· en· W2996602786 on OpenAlexaff
Justin Anderson, Michael B. Kantar, Dan G. Bock, Kunsiri Chaw Grubbs, Edward E. Schilling, Loren H. Rieseberg

Bibliographic record

VenueGenes · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHelianthusBiologyEndangered speciesMonophylyChloroplast DNAEvolutionary biologyPhylogenetic treeBotanyGenomePhylogeneticsCladeSunflowerGeneticsEcologyGeneHorticulture

Abstract

fetched live from OpenAlex

Resolving the origin of endangered taxa is an essential component of conservation. This information can be used to guide efforts of bolstering genetic diversity, and also enables species recovery and future evolutionary studies. Here, we used low-coverage whole genome sequencing to clarify the origin of Helianthus schweinitzii, an endangered tetraploid sunflower that is endemic to the Piedmont Plateau in the eastern United States. We surveyed four accessions representing four populations of H. schweinitzii and 38 accessions of six purported parental species. Using de novo approaches, we assembled 87,004 bp of the chloroplast genome and 6770 bp of the nuclear 35S rDNA. Phylogenetic reconstructions based on the chloroplast genome revealed no reciprocal monophyly of taxa. In contrast, nuclear rDNA data strongly supported the currently accepted sections of the genus Helianthus. Information from combined cpDNA and rDNA provided evidence that H. schweinitzii is likely an allo-tetraploid that formed as a result of hybridization between the diploids Helianthus giganteus and Helianthus microcephalus.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.026
GPT teacher head0.222
Teacher spread0.197 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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