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Record W7041261093

Canola Production

2002· article· en· W7041261093 on OpenAlexaboutno aff

Bibliographic record

VenueOpen PRAIRIE (South Dakota State University) · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaRapeseedErucic acidBrassicaPalatabilityVegetable oilOleic acid
DOInot available

Abstract

fetched live from OpenAlex

Canola is an edible form of rapeseed developed by Canadian plant breeders in the 1970s. Rapeseed and canola are members of the mustard family, which also includes tame and wild mustard, cabbage, cauliflower, kale, and turnip. The term “canola” was registered in 1979 by the Western Canadian Oilseed Crushers Association as the name for rapeseed varieties with genetically modified oil composition and lowered glucosinolates. Canola varieties must have less than 2% erucic acid in the processed oil and less than 30 micromoles of glucosinolates per gram of oil-free meal. The lowered levels of these two seed components enable the oil to be used for human consumption and the meal to be fed to livestock. Canola seed contains about 40% oil and 23% protein. The oil is high in mono- and polyunsaturated fatty acids (oleic, linoleic, and linolenic). The meal contains about 36 to 40% protein after oil extraction and is highly palatable. In contrast, rapeseed oil contains 40% or more erucic acid and is used primarily as an industrial lubricant. The high erucic acid content makes rapeseed oil a poor-quality vegetable oil for human consumption. Rapeseed meal contains glucosinolates that lead to palatability and nutritional problems when formulated into animal feeds. China, Canada, and Europe are the major world producers of canola/rapeseed. U.S. canola production has risen from 199,000 acres in 1993 to over 1.1 million acres in 1998. North Dakota and Minnesota lead the U.S. in canola production.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.421

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1260.075

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 head0.212
Teacher spread0.196 · 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 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

Citations0
Published2002
Admission routes1
Has abstractyes

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