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Record W6980094079

Assessment of genetic diversity of soybean accessions using SSR markers

2022· article· en· W6980094079 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

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 science0.0000.001
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 head0.020
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