Aggressiveness of Three Snow Mold Fungi on Creeping Bentgrass Cultivars under Controlled Environment Conditions
Bibliographic record
Abstract
Snow molds are the most important winter diseases of turfgrass in the United States and Canada. Eight isolates of three snow mold fungal species (three isolates of Typhula ishikariensis, three of T. incarnata, and two of Microdochium nivale) were collected from infected turfgrasses on golf courses. The isolates were evaluated for their relative aggressiveness on three cultivars (L-93, Penncross, and Providence) of creeping bentgrass (Agrostis palustris) under the same controlled conditions. Four plant ages (15, 19, 23 and 27 week-old plants from germination to inoculation) were evaluated for their susceptibility to the three pathogens and for the recovery of the plants. Regardless of age or cultivar of the host plant, M. nivale was found to be more aggressive and faster to infect and colonize than Typhula species. After three weeks recovery, M. nivale-inoculated plants showed higher disease severity than plants inoculated with the two Typhula species. Plants infected by Typhula species displayed no significant difference in disease severity. As creeping bentgrass plants get older, the severity of disease caused by three snow molds gradually decreases. This effect was observed in all cultivars tested, suggesting expression of age-related resistance as the bentgrass plants matured.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".