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Record W2146115856 · doi:10.4141/cjps08179

Influence of alternative management methods on the economics of flax production in the Black Soil Zone

2009· article· en· W2146115856 on OpenAlexvenueno aff
Mohammad Khakbazan, Cynthia A. Grant, R. B. Irvine, Ramona M. Mohr, Debra L. McLaren, M. Monreal

Bibliographic record

VenueCanadian Journal of Plant Science · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaTillageLinumAgronomyCropFertilizerConventional tillageBrassicaMathematicsCrop yieldBiology

Abstract

fetched live from OpenAlex

Studies were conducted at two locations on two Orthic Black Chernozemic soils over 4 yr to evaluate the economic effects of tillage system, preceding crop, phosphorus (P) fertilization of the preceding crop, and P fertilizer application on flax (Linum usitatissimum L.) production. Canola (Brassica napus L.), a non-mycorrhizal crop, and spring wheat (Triticum aestivum L.), a mycorrhizal crop, were grown as the preceding crops under conventional (CT) and reduced tillage (RT) systems, with 0, 11 and 22 kg P ha -1 applied as monoammonium phosphate (MAP). The following year, flax was planted with application of 0 or 11 kg P ha -1 as MAP side-banded at seeding. Tillage method had no impact on the net revenue of wheat or canola at either location when averaged over the 2 yr of study. Net revenue of flax was higher ($32 ha -1 to $95 ha -1 ) when preceded by wheat compared to canola regardless of tillage system or location. Net revenue averaged across the complete crop sequences was higher ($36 ha -1 to $62 ha -1 ) under RT than CT. Lower net revenue variability was also associated with use of RT management, and when wheat was the preceding crop. Changes in commodity prices and input costs had little effect on the relative rankings of the treatments. Flax production with wheat as a preceding crop together with RT and lesser use of P application was the most economical treatment under current input and output prices. Key words: Preceding crops, tillage, p fertilizer, net revenue

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)0.001
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 score0.842
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.029
GPT teacher head0.255
Teacher spread0.226 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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