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Record W3154347492 · doi:10.1139/cjps-2020-0260

Baseline survey of herbicide resistance in Russian thistle (<i>Salsola tragus</i> L.) finds no resistance in Manitoba

2021· article· en· W3154347492 on OpenAlexafffundvenueabout
Charles M. Geddes, Robert H. Gulden, Tammy Jones, Julia Y. Leeson, Mattea M. Pittman, Shaun M. Sharpe, Scott W. Shirriff, Hugh J. Beckie

Bibliographic record

VenueCanadian Journal of Plant Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of ManitobaAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaAlberta Wheat CommissionSaskatchewan Canola Development CommissionWestern Grains Research Foundation
KeywordsThistleGlyphosateAcetolactate synthaseHerbicide resistanceResistance (ecology)AgronomyBiologyWeed

Abstract

fetched live from OpenAlex

Recent confirmations of glyphosate-resistant Russian thistle (Salsola tragus L.) in Montana, Washington, and Oregon, warrant greater surveillance of herbicide-resistant Russian thistle in western Canada. A randomized-stratified survey of 315 sites in Manitoba was conducted in 2018 to determine the incidence of herbicide resistance in Russian thistle and other weeds sampled post-harvest. Russian thistle populations were collected from 14 of the 315 sites surveyed. None of these populations exhibited resistance to acetolactate synthase inhibitors (tribenuron/thifensulfuron), synthetic auxins (2,4-D ester or fluroxypyr), or glyphosate. This Manitoba survey of herbicide-resistant Russian thistle serves as a baseline for future surveillance efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.668

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.214
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes4
Has abstractyes

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