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Record W2067454365 · doi:10.4141/p01-178

Response of wild oat (<i>Avena fatua</i>) to residual and non-residual herbicides in canola (<i>Brassica napus</i>) in western Canada

2002· article· en· W2067454365 on OpenAlexvenueaboutno aff
Hugh J. Beckie, F.A. Holm

Bibliographic record

VenueCanadian Journal of Plant Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAvena fatuaCanolaAgronomyBrassicaAvenaResidualGlufosinateBiologyWeedGlyphosateMathematics

Abstract

fetched live from OpenAlex

It has been stated that soil residual herbicides, by controlling successive flushes of weeds, increase effective kill (efficacy) over the growing season, and thus impose a higher selection pressure for resistance in weeds than non-residual herbicides. To investigate this issue, the responses of wild oat to increasing rates of residual and non-residual herbicides in canola and wild oat recruitment in the following year were examined in a field study conducted in Saskatchewan, Canada, from 1997 to 2000. The rate-response curves of the wild oat variables indicated that efficacy of the soil residual herbicides, ethalfluralin and triallate, and of the non-residual herbicide, glufosinate, was generally lower than that of imazamox/imazethapyr (residual), sethoxydim, and glyphosate (non-residual). Emergence of wild oat in spring wheat (Triticum aestivum L.) grown in the following year did not differ among herbicides applied in the preceding crop year, nor was there a significant herbicide by rate interaction. The results suggest that the soil residual activity o f these herbicides does not strongly influence selection pressure, estimated by reduction in wild oat seed return in canola. Key words: Brassica napus, Avena fatua, selection pressure, herbicide resistance

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 score0.809
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.194
Teacher spread0.181 · 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

Citations3
Published2002
Admission routes2
Has abstractyes

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