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Record W2006891580 · doi:10.7202/706068ar

Mechanisms of cross and multiple herbicide resistance in Alopecurus myosuroides and Lolium rigidum

2005· article· en· W2006891580 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsQuebec Society for the Protection of PlantsUniversité de MontréalUniversity of Alberta
Fundersnot available
KeywordsLolium rigidumCross-resistanceBiologyResistance (ecology)WeedAgronomyPopulationHerbicide resistanceGenetics

Abstract

fetched live from OpenAlex

Alopecurus myosuroides and Lolium rigidum have developed resistance to herbicides with several modes of action in many herbicide classes. A. myosuroides biotype Peldon A1 from England exhibits non-target site cross resistance to substituted urea and aryloxyphenoxypropionate herbicides (APP) due to enhanced metabolism. L. rigidum biotype SLR 31 from Australia has multiple resistance mechanisms, including both non-target site cross resistance and target site cross resistance. The majority of the SLR 31 population has enhanced metabolism of chlorsulfuron and diclofop-methyl and a mechanism correlated with altered plasma membrane response, which correlates with resistance to some APP and cyclohexanedione (CHD) herbicides. A small proportion of the population also has target site cross resistance to APP and CHD herbicides. While A myosuroides and L. rigidum share common biological elements, they are not unique. Non-target site cross resistance and multiple herbicide resistance is predicted to develop in other weed species. The repercussions of cross and multiple resistance warrant proactive measures to prevent or delay onset.

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.

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 score0.905
Threshold uncertainty score0.995

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 studies0.0000.000
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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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