MétaCan
Menu
Back to cohort
Record W7014618834

Plastid genome sequencing reveals biogeographical structure and extensive population genetic variation in wild populations of Phalaris arundinacea L. in north‐western Europe

2020· other· en· W7014618834 on OpenAlexfundno aff

Bibliographic record

VenueArrow@dit (Dublin Institute of Technology) · 2020
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
FundersFP7 Food, Agriculture and Fisheries, BiotechnologyInstitute of GeneticsTrinity College Dublin
KeywordsGenetic diversityGenetic variationPopulationGenetic structureGenomeGenetic variabilityPopulation geneticsGene flowMicrosatellite
DOInot available

Abstract

fetched live from OpenAlex

New and comprehensive collections of the perennial rhizomatous reed canary grass (Phalaris arundinacea) were made in NW Europe along north‐to‐south and east‐to‐west clines from Denmark, Germany, Ireland, Poland, Sweden and the United Kingdom. Rhizome, seed and leaf samples were taken for analysis and genetic resource conservation. A subsample covering the geographical range was characterized using plastid genome sequencing and SNP discovery generated using a long‐read PCR and MiSeq sequencing approach. Samples were also subject to flow cytometry and all found to be tetraploid. New sequences were assembled against a Lolium perenne (perennial ryegrass) reference genome, and an average of approximately 60% of each genome was aligned (81 064 bp). Genetic variation was high among the 48 sequenced genotypes with a total of 1793 SNPs, equating to 23 SNPs per kbp. SNPs were subject to principal coordinate and Structure analyses to detect population genetic groupings and to examine phylogeographical pattern. Results indicate substantial genetic variation and population genetic structuring of this allogamous species at a broad geographical scale in NW Europe with plastid genetic diversity organized more across an east‐to‐west than a north‐to‐south cline.

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 score0.170
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.018
GPT teacher head0.214
Teacher spread0.196 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueArrow@dit (Dublin Institute of Technology)Same topicBioenergy crop production and managementFrench-language works237,207