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Record W2340620563 · doi:10.15258/sst.2016.44.1.01

Multiplexed SSR markers for identification and purity assessment of Canadian flax varieties

2016· article· en· W2340620563 on OpenAlexaboutno aff
Daniel J. Perry, Sang-sup Lee

Bibliographic record

VenueSeed Science and Technology · 2016
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyIdentification (biology)BotanyGenetic markerMicrosatelliteBiotechnologyGeneticsAlleleGene

Abstract

fetched live from OpenAlex

A multiplexed set of SSR markers was assembled which, in combination with DNA extraction from individual seeds, provides a practical means to identify Canadian flax varieties and may be useful for assessment of seed purity. Seven SSR markers were chosen based upon their joint ability to discriminate among varieties and, following selection of alternative primers for three of the markers, were combined into a single multiplex with no overlap of allele sizes. A survey of 120 seeds of each of 23 registered Canadian flax varieties indicated that polymorphism within varieties was common and may add a layer of complexity to variety identification and, in particular, to seed purity analysis. Examination of large numbers of individual reference seeds is recommended when constructing databases to ensure that polymorphism that may exist within varieties is sufficiently represented.

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)0.001
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 score0.399
Threshold uncertainty score0.804

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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

Citations2
Published2016
Admission routes1
Has abstractno

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