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Record W7093386836

Mustard

2010· other· W7093386836 on OpenAlexaboutno aff

Bibliographic record

VenueNDSU Repository (North Dakota State University) · 2010
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSeedbedSowingMustard seedLoamCropWhite mustardMustard Plant
DOInot available

Abstract

fetched live from OpenAlex

There are three types of mustard, yellow, brown and oriental.Yellow mustard (Brassica hirta) is the most commonly grown in North Dakota.Only small acreages of brown and oriental (Brassica juncea) are grown in North Dakota.Yellow mustard is used mainly to produce "mild" prepared mustard for table use.It is also used in salad dressings, pickles and processed meat products.Brown and oriental mustard are used mainly for "hot" table mustard, and some for oil and spices.Amount of mustard planted in North Dakota has been in the range of 10,000 to 60,000 acres.North Dakota mustard acreage was 10,000 in 1990 and 14,000 in 1991, compared to 19,691 acres in the United States in 1987.Harvested wheat acreage in 1991 for North Dakota was 9.8 million and 57.7 million for the United States.Mustard is best adapted to fertile and well-drained soils.Avoid dry, sandy loam soils.Mustard has some tolerance to salinity and is similar to barley in its productivity on saline soils.Yellow mustard varieties mature in 80 to 85 days; the brown and oriental types require about 90 to 95 days to reach maturity.A seedbed for mustard should have no previous crop residue and be firm and fairly level.Shallow tillage, deep enough to kil weeds, will keep soil moisture close to the surface and leave the seedbed firm.This will permit shallow seeding and encourage rapid, uniform emergence.Seedbeds should be packed before planting with a roller packer, empty press drill or rodweeder.Some producers are successfully planting mustard into standing small grain stubble and into minimum tilled stubble.The firm moist seedbed has been providing good stands.Yellow mustard varieties tend to be shorter, earlier maturing, and lower yielding than brown or oriental varieties.The variou seed varieties are available from contracting firms.Varieties of yellow mustard include Gisilba, Ochre and Tilney.Oriental mustard varieties include Cutless, Forge and Lethbridge 22. Brown mustard varieties include Blaze and Common Brown.

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), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.344
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.004
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0050.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0160.027

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 head0.006
GPT teacher head0.168
Teacher spread0.162 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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