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Record W2023934143 · doi:10.4141/p03-054

Influence of variable rates of imazamethabenz and difenzoquat on wild oat (<i>Avena fatua</i>) seed production, and wheat (<i>Triticum aestivum</i>) yield and profitability

2003· article· en· W2023934143 on OpenAlexaffvenueabout
John T. O’Donovan, K. Neil Harker, Robert E. Blackshaw, R. N. Stougaard

Bibliographic record

VenueCanadian Journal of Plant Science · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAvena fatuaAgronomyYield (engineering)BiologyWeedAnimal science

Abstract

fetched live from OpenAlex

Field experiments to investigate the effects of variable imazamethabenz rates on wild oat seed production and wheat yield and profitability were conducted at Lacombe, Lethbridge and Vegreville, Alberta, and Kalispell, Montana, over several years. Similar studies with difenzoquat were conducted at Lacombe and Lethbridge. In most cases, reducing the herbicide rates below those recommended resulted in increases in wild oat seed production, but the potential for returning relatively large amounts of wild oat seed to the soil seedbank depended on the extent of the rate reduction. For example, averaged over locations and years, reducing the rate of imazamethabenz to 75% of the recommended rate resulted in wild oat seed production increasing by 25% compared with an increase of over 100% when the rate was reduced to 50%. Wheat yields and economic returns as functions of rate also varied for both herbicides. It was more economical, in most cases, to apply imazamethabenz at 50 or 75% of the recommended rate compared with the full rate. However, an economic loss occurred in four and three of the 11 location-years when the imazamethabenz rate was reduced to 50 and 75%, respectively, and losses were more severe at the 50% rate. Compared with imazamethabenz, reducing the rate of difenzoquat tended to be more risky in terms of increased wild oat seed production and reduced net economic return. Key words: Reduced herbicide rates

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)0.001
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 score0.814
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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

Citations13
Published2003
Admission routes3
Has abstractyes

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