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Record W4224805285 · doi:10.1094/php-02-22-0012-br

Fungicide Efficacy During a Severe Epidemic of Tar Spot on Corn in the United States and Canada in 2021

2022· article· en· W4224805285 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePlant Health Progress · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFungal Plant Pathogen Control
Canadian institutionsMinistry of Agriculture, Food and Rural AffairsUniversity of Guelph
FundersIndiana Corn Marketing CouncilGrain Farmers of Ontario
KeywordsFungicideBiologytar (computing)HorticultureTasselYield (engineering)Leaf spotAgronomyToxicologyZea mays

Abstract

fetched live from OpenAlex

A 2021 epidemic of tar spot of corn caused by Phyllachora maydis led to significant yield losses in the midwestern United States and Ontario, Canada. Uniform fungicides trials consisting of nine foliar fungicides applied at the tassel (VT) or silk (R1) growth stage were evaluated for tar spot management in five field trials in the midwestern United States and Ontario, Canada, in 2021. All nine foliar fungicide treatments significantly reduced tar spot severity, but only Delaro Complete (prothioconazole + fluopyram + trifloxystrobin), Revytek (mefentrifluconazole + pyraclostrobin + fluxapyroxad), and Veltyma (mefentrifluconazole + pyraclostrobin) protected yield compared with the nontreated 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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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