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Record W225014367

Identification of Canadian six row barley (Hordeum vulgare L.) cultivars with primers derived from STSs obtained from RAPD diagnostic bands.

2000· article· en· W225014367 on OpenAlexaboutno aff
Bernard R. Baum, Subbaiah Mechanda, Vahab D. Soleimani

Bibliographic record

VenueSeed Science and Technology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsRAPDBiologyHordeum vulgareIdentification (biology)GeneticsCultivarPolymerase chain reactionBotanyPoaceaeGeneGenetic diversity
DOInot available

Abstract

fetched live from OpenAlex

To address the general concern about reproducibility of diagnostic DNA bands obtained from RAPDs for the identification of the six row Canadian barley cultivar identification scheme, we have designed specific primers based on STSs derived from those diagnostic bands. Furthermore, we have also optimized the PCR reaction conditions of the identification primers to maximize reliability. These conditions were used to develop a computerized identification key suitable for the Canadian grain handling system. Co-migrating bands pose a problem in the conversion of RAPD diagnostics to STSs. There is a need to sample and sequence a number of clones, although the number of clones theoretically needed has not been addressed. Up to seven clones of each of the diagnostic bands were sequenced. A match of at least two sequences was considered representative of the diagnostic band. However, when two groups of sequences were found with similar size in base pairs, two STSs were established for the same diagnostic band. The majority of the STSs were found to be characteristically repetitive sequences, indicating the nature of target sequences of the RAPD primers. Future work towards higher diagnostic efficiency needed in support of the Canadian grain handling system is discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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