Recovery Plan for Tar Spot of Corn, Caused by Phyllachora maydis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".