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Record W2153501987 · doi:10.5539/jas.v5n5p158

Response of Nebraska Horseweed (Conyza canadensis) Populations to Dicamba

2013· article· en· W2153501987 on OpenAlexvenueno aff
Roberto Crespo, Mark L. Bernards, Greg R. Kruger, Donald Lee, Rob Wilson

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDicambaBiologyGlyphosateAgronomyWeedHerbicide resistanceWeed controlDry weight

Abstract

fetched live from OpenAlex

Dicamba-resistant soybeans are being developed to provide an additional herbicide mechanism-of-action for postemergence weed control in soybean. Numerous broadleaf species, including horseweed, have evolved resistance to glyphosate. It is anticipated that dicamba will be used by farmers as a primary tool to manage these weeds. Studying and understanding variability in horseweed response to dicamba will aid in developing appropriate risk management strategies to extend the utility of the dicamba-resistance technology. Horseweed plants from ten Nebraska populations were treated with one of nine doses of dicamba in greenhouse experiments. At 28 days after treatment (DAT) visual injury estimations were made and plants were harvested to determine dry weight. There was a three-fold difference in the I90 (90% visual injury estimate) between the least (638 g ha-1) and most (205 g ha-1) susceptible populations. Two plants from five populations were observed for an additional three months. No plants treated at doses above 280 g ha-1 survived to set seeds. These results suggest that maintaining use doses of 560 g ha-1 or greater may fully control horseweed populations from Nebraska and minimize the risk of plants surviving to set seed, in addition to practicing other proven herbicide-resistance management strategies.

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)0.001
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 score0.986
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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