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Record W1989012180 · doi:10.4236/as.2013.412087

Response of cranberry and kidney beans to linuron

2013· article· en· W1989012180 on OpenAlexafffundabout
Nader Soltani, Christy Shropshire, Peter H. Sikkema

Bibliographic record

VenueAgricultural Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of Guelph
FundersAgricultural Adaptation Council
KeywordsCultivarHorticultureDry beanShootBiologyBotany

Abstract

fetched live from OpenAlex

Field studies were conducted in 2009 and 2010 at the Huron Research Station, Exeter, Ontario and the University of Guelph Ridgetown Campus, Ridgetown, Ontario to determine the tolerance of four cultivars of cranberry bean (“Etna”, “Hooter”, “SVM Taylor”, and “Capri”) and four cultivars of kidney bean (“Red Hawk”, “Pink Panther”, “Calmont”, and “Majesty”) to linuron applied preemergence at 1125 and 2250 g·ai·ha-1. One week after emergence (WAE), linuron applied PRE caused 0.4% to 1.2% injury in “Etna”, “Hooter”, “SVM Tayler”, and “Capri” cranberry bean and 3.1% to 3.6% injury in “Red Hawk”, “Pink Panther”, “Calmont”, and “Majesty” kidney bean. At 2 and 4 WAE, there was no difference in injury among the dry bean cultivars. Contrast comparing injury due to linuron in cranberry vs kidney bean cultivars indicated 2.3%, 1.7%, and 1.2% greater injury in kidney bean compared to cranberry bean at 1, 2, and 4 WAE, respectively. Linuron PRE caused slightly greater injury in kidney bean compared to cranberry bean but crop injury was minimal with no adverse effect on plant height, shoot dry weight, seed moisture content, and yield under the environments evaluated. Based on this research, linuron applied PRE at the proposed rate of 1125 g·ai·ha-1 can be safely used in cranberry and kidney beans 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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

Citations1
Published2013
Admission routes3
Has abstractyes

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