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Record W2093690344 · doi:10.4141/p02-083

Sulphur fertilizer and tillage management of canola and wheat in western Canada

2004· article· en· W2093690344 on OpenAlexafffundvenueabout
Cynthia A. Grant, Adrian Johnston, George W. Clayton

Bibliographic record

VenueCanadian Journal of Plant Science · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsPotashCorp (Canada)Agriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsCanolaTillageAgronomyYield (engineering)FertilizerTigerConventional tillageCropBrassicaEnvironmental scienceChemistryBiologyMathematicsMaterials science

Abstract

fetched live from OpenAlex

A 3-yr field study in Manitoba, Saskatchewan and Alberta evaluated immediate and residual effects of source, timing and placement of sulphur fertilizers on canola (Brassica napus L.) and wheat (Triticum aestivumL.) under conventional (CT) and reduced tillage (RT). Sulphur fertilization did not increase wheat yield, even when soil sulphate was low. Ammonium sulphate (AS) and ammonium thiosulphate (ATS) increased canola yield in 2 of 3 yr at the Saskatchewan site while elemental S and Tiger 90™ did not. Residual S from AS and ATS increased canola yield on S-deficient soils in the second and third crops after application. Canola yield on the S-deficient soil was lower where broadcast Tiger 90 rather than AS or ATS was applied the previous year, indicating that broadcast Tiger 90 oxidation was insufficient to support canola yield in the second crop year after application. Banding or seed-placing Tiger 90 delayed oxidation further. In the third crop after application, canola yield was similar with broadcast Tiger 90, AS or ATS but was lower with seed-placed or banded Tiger 90 than AS or broadcast Tiger 90. Small particle size and broadcast application of elemental S are needed to hasten oxidation of S to sulphate-S. Key words: Elemental S, Bentonite S, zero tillage, reduced tillage

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.829

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)0.0000.000

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 head0.198
Teacher spread0.193 · 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 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

Citations30
Published2004
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Plant ScienceSame topicNitrogen and Sulfur Effects on BrassicaFrench-language works237,207