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Record W6922097034 · doi:10.1139/cjps-2015-100

AAC Adagio yellow mustard

2015· article· en· W6922097034 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsnot available
Fundersnot available
KeywordsMucilageCultivarMustard seedMustard PlantPlant cultivation

Abstract

fetched live from OpenAlex

Cheng, B., Rakow, G., Olson, T., Williams, D. J. and Gugel, R. K. 2015. AAC Adagio yellow mustard. Can. J. Plant Sci. 95: 1043-1045. Mucilage content in yellow mustard (Sinapis alba L.) is an important seed quality parameter for the mustard trade since mucilage contributes to the consistency of prepared mustard products. Some wild type brown-seeded accessions of S. alba have much higher mucilage contents than have been observed in yellow-seeded cultivars and breeding lines. Increasing the mucilage content of cultivated, yellow-seeded S. alba by transferring the high mucilage trait from brown-seeded S. alba was initiated in 2004 at the Saskatoon Research Centre, Agriculture and Agri-Food Canada. The yellow mustard variety AAC Adagio with high mucilage content [96.8 centistokes (cst) g-1 seed] was successfully developed from crosses between the elite yellow-seeded breeding line SA00-PYM (mucilage: 35.2 cst g-1 seed) and five brown-seeded S. alba accessions (mucilage: 87.5-108.7 cst g-1 seed). AAC Adagio is well-adapted to all mustard growing areas of western Canada.

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 categoriesMeta-epidemiology (narrow)
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 score0.673
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.264
GPT teacher head0.255
Teacher spread0.009 · 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.

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
Published2015
Admission routes1
Has abstractyes

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