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Record W3059508458 · doi:10.1017/wet.2020.93

Time-of-day effect on weed control efficacy with tolpyralate plus atrazine

2020· article· en· W3059508458 on OpenAlexaff
Nicole M. Langdon, Nader Soltani, Alan J. Raedar, David C. Hooker, Darren E. Robinson, Peter H. Sikkema

Bibliographic record

VenueWeed Technology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLambsquartersAtrazineFoxtailWeedWeed controlRagweedAgronomyBiologyHorticulturePesticideChenopodium

Abstract

fetched live from OpenAlex

Abstract Tolpyralate is a new 4-hydroxyphenyl-pyruvate dioxygenase (HPPD)–inhibiting herbicide for weed control in corn. Previous research has reported efficacy of tolpyralate + atrazine on several annual grass and broadleaf weed species; however, no studies have evaluated weed control of tolpyralate + atrazine depending on time-of-day (TOD) of application. Six field experiments were conducted over a 2-yr period (2018, 2019) near Ridgetown, ON, to determine if there is an effect of TOD of application on tolpyralate + atrazine efficacy on common annual grass and broadleaf weeds. An application was made at 3-h intervals beginning at 06:00 h with the last application at 24:00 h. There was a slight TOD effect on velvetleaf, pigweed species, and common ragweed control with tolpyralate + atrazine; however, the magnitude of change throughout the day was ≤3% at 2, 4, or 8 wk after application (WAA). There was no effect of TOD of tolpyralate + atrazine on the control of lambsquarters, barnyardgrass, and green foxtail. All weed species were controlled ≥88% at 8 WAA. There was no effect of TOD of tolpyralate + atrazine application on corn yield. Results of this study show no evidence of a TOD effect on weed control efficacy with tolpyralate + atrazine.

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 score0.725
Threshold uncertainty score0.514

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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