Review of <i>Pythium</i> Species Causing Damping-Off in Corn
Bibliographic record
Abstract
Seedling blights and root rots caused by Pythium species account for almost US$25 million in annual losses to corn (Zea mays) production in the United States and Ontario. Variations in annual rainfall and increasing use of no-till agriculture can favor soilborne pathogens like Pythium. To date, 44 species have been reported as pathogenic to corn in the United States. The average annual corn planting date in the United States has shifted approximately 1 week earlier in the past decade, exposing young corn plants to longer germination periods of generally cooler temperatures, favoring attack by Pythium. Optimal temperatures, aggressiveness, and response to chemical and biological treatment options vary by species. This review consolidates the species of Pythium reported as corn pathogens in literature to date. It also provides an insight into management strategies and discusses variations in fungicide sensitivity observed in corn-related Pythium species.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".