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Record W3203762183 · doi:10.5376/mpb.2021.12.0030

Development of Polymorphic SSR Markers in <i>Vallisneria</i> Based on RAD seq

2021· article· en· W3203762183 on OpenAlexvenueno aff
Meng How Tan, Yuxin Shi, Haisu Zheng, Liu Shao, Peimin He

Bibliographic record

VenueMolecular Plant Breeding · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Species Descriptions
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyInbreedingGeneticsMicrosatelliteLoss of heterozygosityAlleleGenePopulation

Abstract

fetched live from OpenAlex

Vallisneria belongs to Hydrocharitaceae, which is a pioneer species of ecological restoration in waters. In order to carry out a more comprehensive SSR analysis of Vallisneria , we used the restriction-site associated DNA sequencing (RAD-seq) technology to analyze Simple Sequence Repeats (SSR) information of Vallisneria , SSR markers and primer of Vallisneria were developed based on RAD-seq data.Among which ,366 simple sequence repeats (SSR) loci were detected. Primers of 355 loci were designed successfully, and the two base repeat type SSR loci were the largest (59.56%). Finally, we confirmed 23 pairs of polymorphic SSR primers after the screening and validation. The analysis results by Genepop software showed that the mean number of alleles of the 23 loci is 3.26, and these loci do not link to each other (P<0.01). Four loci deviate from HWE (P<0.01) and the number of heterozygous roughly the same as that of homozygotes (observed heterozygosity mean of 0.460), inbreeding coefficient is high (mean of 0.880). Which could be caused by take sample too closely in the same sampling, and Vallisneria have a combination of generative propagation and clone.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.005

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 head0.016
GPT teacher head0.206
Teacher spread0.189 · 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 designBench or experimental
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

Citations0
Published2021
Admission routes1
Has abstractyes

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