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Record W3183190846 · doi:10.1094/php-04-21-0074-rp

Recovery Plan for Tar Spot of Corn, Caused by <i>Phyllachora maydis</i>

2021· article· en· W3183190846 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePlant Health Progress · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of GuelphMinistry of Agriculture, Food and Rural Affairs
FundersAgricultural Research ServiceFoundation for Food and Agriculture ResearchIndiana Corn Marketing CouncilU.S. Department of Agriculture
Keywordstar (computing)BushelLeaf spotGeographyBiologyYield (engineering)Agronomy

Abstract

fetched live from OpenAlex

Tar spot is a foliar disease of corn threatening production across the Americas. The disease was first documented in Mexico in 1904 and is now present in 15 additional countries throughout Central America, South America, and the Caribbean. Researchers and growers in Central America, South America, and the Caribbean consider tar spot to be a disease complex caused by multiple fungal pathogens. When environmental conditions are conducive for infection, these regions have experienced yield losses that can reach up to 100%. In 2015, tar spot was detected in the United States for the first time in Illinois and Indiana. Since that time tar spot has spread across the U.S. corn-growing region, and the disease has been found in Florida, Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, Pennsylvania, and Wisconsin. In 2020, tar spot was also found in southwest Ontario, Canada. Losses in the United States due to tar spot totaled an estimated 241 million bushels from 2018 to 2020. With the potential to continue to spread across the U.S. corn-growing states, much greater losses could result when environmental conditions are conducive.

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)0.000
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 score0.378
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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