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Record W2918692527 · doi:10.1139/cjps-2018-0320

Efficacy of HPPD-inhibiting herbicides applied preemergence or postemergence for control of multiple herbicide resistant waterhemp [<i>Amaranthus tuberculatus</i> (Moq.) Sauer]

2019· article· en· W2918692527 on OpenAlexaffvenue
Lauren Benoit, Nader Soltani, David C. Hooker, Darren E. Robinson, Peter H. Sikkema

Bibliographic record

VenueCanadian Journal of Plant Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMesotrioneAtrazineBiologyWeed controlWeedAgronomyDicambaPesticide

Abstract

fetched live from OpenAlex

Research was conducted in 2017 and 2018 to determine the relative efficacy of five HPPD-inhibitors, tank-mixed with atrazine, for the control of multiple herbicide resistant waterhemp. At 12 wk after application (WAA), isoxaflutole + atrazine, mesotrione + atrazine, and tembotrione + atrazine, applied preemergence (PRE), controlled waterhemp 90%, 87%, and 81%, respectively. None of the HPPD-inhibiting herbicides applied PRE controlled waterhemp similar to the weed-free control 12 WAA. Applied postemergence, topramezone + atrazine, mesotrione + atrazine, tolpyralate + atrazine, and tembotrione + atrazine controlled waterhemp 87%, 94%, 97%, and 98% 12 WAA, respectively, and were all similar to the weed-free control.

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 score0.522
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.211
Teacher spread0.196 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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