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Record W4360615136 · doi:10.1017/wet.2023.13

Glyphosate-resistant downy brome (<i>Bromus tectorum</i>) control using alternative herbicides applied postemergence

2023· article· en· W4360615136 on OpenAlexafffundabout
Charles M. Geddes, Mattea M. Pittman

Bibliographic record

VenueWeed Technology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaWestern Grains Research FoundationSaskatchewan Wheat Development CommissionAlberta Wheat CommissionMinistry of Agriculture - Saskatchewan
KeywordsBromus tectorumGlufosinateAgronomyGlyphosateBiologyWeed controlWeedBentazonPesticide resistanceDowny mildewClopyralidAcetolactate synthasePesticide

Abstract

fetched live from OpenAlex

Abstract Downy brome is a troublesome facultative winter-annual grass weed that invades agricultural and nonagricultural lands in western North America and can cause substantial crop yield losses particularly in no-till winter wheat. Glyphosate-resistant (GR) downy brome was identified in southern Alberta in 2021, representing the first confirmation of a GR grass weed in Canada. This study was designed to evaluate alternative herbicides and herbicide mixtures applied postemergence (POST) for control of GR and glyphosate-susceptible (GS) downy brome populations at the seedling stage under a controlled environment. The GR downy brome did not exhibit cross-resistance to other herbicides applied POST. Quizalofop alone or in combination with imazamox, imazamox + bentazon, or imazamox/imazethapyr, and glufosinate mixed with either clethodim or tiafenacil resulted in ≥80% visible control, plant mortality, and reduction in biomass of both GR and GS downy brome populations 21 d after treatment. Diligent stewardship of these remaining herbicide options is warranted since downy brome populations with resistance to herbicides that inhibit acetyl-CoA carboxylase or acetolactate synthase have been reported in neighboring states.

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 score0.716
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.018
GPT teacher head0.229
Teacher spread0.212 · 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

Citations7
Published2023
Admission routes3
Has abstractyes

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