Compost Tea for the Management of Dollar Spot (Sclerotinia homoeocarpa) on Turfgrass
Bibliographic record
Abstract
Turfgrasses are unique in their capability of tolerating foot traffic and physical wear, while still remaining functional and aesthetically pleasing. Fungal disease represents one of the most common limiting factors in managing turf for economical purposes. Dollar spot (Sclerotinia homoeocarpa F.T. Bennett) represent one of the most common and persistent fungal diseases of turf grasses here in the Maritime Provinces. The results demonstrated the potential of compost tea (CT) to negate the harmful effects of the fungal toxic metabolite produced during a dollar spot infection, as well the teas showed to increase the activity of defense enzymes as compared to the control. The field study showed the potential for mink compost tea (M-CT) to control disease but its efficacy was site specific and quite variable. Finally the teas were determined to be quite consistent in composition and four secondary metabolites were determined to be present in the teas.
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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) | 0.001 | 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".