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Record W6980094079

Assessment of genetic diversity of soybean accessions using SSR markers

2022· article· en· W6980094079 on OpenAlexaboutno aff

Bibliographic record

VenueFiVeR (Institute of Field and Vegetable Crops, Novi Sad, Serbia) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsnot available
Fundersnot available
KeywordsGenetic diversityUPGMADomesticationGenetic variationGenotypeMicrosatelliteGenetic markerGene poolGenetic relationship
DOInot available

Abstract

fetched live from OpenAlex

Soybean is a plant species characterized by an extremely narrow genetic base, as a consequence of self-pollination, a long process of domestication and artificial selection. A key phase in maintaining diversity and successful utilization in breeding is the genetic and phenotypic characterization of accessions available in collections. Soybean collection in Maize Research Institute "Zemun Polje" maintains more than 500 accessions from different regions of the world. The aim of this study was to investigate the level of genetic variation in collection, through the sample of 90 soybean genotypes originated from 15 countries, classified in 5 geographical groups (DOM-Serbia, EUR-European, USA-North American, CAN- Canadian, EXO-China and Japan). Twenty SSR primer pairs were selected for the molecular analysis. To assess the genetic relations among accessions, cluster analysis employing UPGMA method was performed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
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
Bibliometrics0.0020.001
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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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
Published2022
Admission routes1
Has abstractyes

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