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Record W2766606852 · doi:10.1139/cjps-2016-0371

Glyphosate- and multiple-resistant waterhemp (Amaranthus tuberculatus var. rudis) in Ontario, Canada

2017· article· en· W2766606852 on OpenAlexaffvenueabout
Mike G. Schryver, Nader Soltani, David C. Hooker, Darren E. Robinson, Patrick J. Tranel, Peter H. Sikkema

Bibliographic record

VenueCanadian Journal of Plant Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGlyphosateBiologyPesticide resistanceAgronomyAtrazinePopulationPesticideGlufosinateHerbicide resistanceWeed

Abstract

fetched live from OpenAlex

Waterhemp is one of the most troublesome weeds in the US and is spreading into Ontario. In 2014, a waterhemp population was not controlled with glyphosate in a field in Lambton County, ON. This population was the first confirmed glyphosate-resistant (GR) waterhemp in Canada. In 2015, waterhemp seeds were collected from 48 fields in Lambton (32), Chatham-Kent (2), and Essex (14) counties to determine the occurrence and distribution of GR waterhemp in Ontario. Waterhemp plants were grown in a greenhouse and sprayed when 10 cm in height. In addition to glyphosate (a group 9 herbicide), collected populations were screened for resistance to imazethapyr and atrazine, representing herbicide groups 2 and 5, respectively. Visual control estimates for biomass reduction were completed at 1, 3, and 5 wk after application. Glyphosate-resistant waterhemp was confirmed in 40 fields, representing 82% of all sampled fields from the three Ontario counties. Of the 49 populations collected, all were resistant to imazethapyr (group 2) and 76% were resistant to atrazine (group 5). Of all the populations tested, 61% of all samples were found to be resistant to all three herbicide groups. This study is the first to confirm GR waterhemp in Ontario.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.183
Teacher spread0.170 · 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

Citations27
Published2017
Admission routes3
Has abstractyes

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