Tar Spot of Corn: A Diagnostic and Methods Guide
Bibliographic record
Abstract
Tar spot of corn is an emerging plant disease in the continental United States and Canada caused by the fungal pathogen Phyllachora maydis Maubl. Tar spot has been known to occur in Mexico, the Caribbean, and Central and South America since the early to mid-1900s. In 2015, it was reported for the first time in the continental United States. Since that time, tar spot has spread across corn-producing areas in the United States with epidemics as recent as 2021 resulting in significant yield losses. Although tar spot has been known to affect corn for over a century in the Americas, the biology of the pathogen, etiology, and epidemiology of the disease are not well understood. Additionally, symptoms and signs of tar spot resemble other foliar diseases and abiotic disorders of corn, which may lead to misdiagnosis. In this paper, we provide a brief description of current knowledge about tar spot of corn, including pathogen taxonomy, host range, symptoms and signs, specimen storage, pathogenicity testing, diagnostic protocols, and geographic distribution. This information will be useful to diagnosticians, researchers, and other professionals working with this disease.
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.079 |
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".