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White bean (<i>Phaseolus vulgaris</i>) tolerance to preplant‐incorporated herbicides

2005· article· en· W1966648794 on OpenAlexaffabout
Nader Soltani, Peter H. Sikkema

Bibliographic record

VenueWeed Biology and Management · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMetolachlorPhaseolusShootAgronomyBiologyDry weightCultivarDry beanHorticulturePesticideAtrazine

Abstract

fetched live from OpenAlex

There is a limited number of registered herbicides in white beans. Field trials were conducted at two Ontario, Canada, locations (Exeter and Ridgetown) in 2001 and 2002 to evaluate tolerance of two white bean cultivars, AC Compass and OAC Thunder, to preplant‐incorporated applications of S ‐metolachlor plus imazethapyr (1600 + 75 and 3200 + 150 g ai ha −1 , respectively), flumetsulam plus S ‐metolachlor ( premixed at 1443 and 2886 g ai ha −1 ) and cloransulam‐methyl (35 and 70 g ai ha −1 ). There were no differences between the two cultivars in their responses to the herbicide treatments. S ‐metolachlor plus imazethapyr caused as much as 5% visual crop injury and decreased plant height up to 20%, shoot dry weight up to 39% and yield as much as 21%. Flumetsulam plus S ‐metolachlor caused as much as 7% visual crop injury and reduced plant height by up to 25%, shoot dry weight by up to 46% and yield as much as 24%. Cloransulam‐methyl caused as much as 10% visual crop injury and decreased plant height up to 35%, shoot dry weight up to 55% and yield as much as 44%. There were no differences in seed moisture content among any of the herbicide treatments. This research suggests that the margin of safety of white bean is inadequate to support the preplant‐incorporated registration of S ‐metolachlor plus imazethapyr, flumetsulam plus S ‐metolachlor and cloransulam‐methyl 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.262

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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 designNot applicable
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

Citations12
Published2005
Admission routes2
Has abstractyes

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