Use of biosolids as a potential fertilizer for lawn turf
Bibliographic record
Abstract
Abstract Ensuring turfgrass health through an effective fertilization program is crucial for stress tolerance and overall vigor. The use of organic fertilizers, in particular biosolids, has emerged as a promising alternative to mitigate the negative impacts associated with traditional inorganic fertilizers and to offer a sustainable and eco‐friendly approach to maintaining turfgrass health. The objective of this research was to investigate the potential of biosolids as a sole or supplemental source of fertilizer to improve turfgrass health. Two field trials were conducted in Guelph, ON, from 2018 to 2020. Fertilizer treatments consisted of a negative control with no fertilizer, two inorganic controls, and three organic fertilizers, two of which were biosolids, applied via topdressing either two or three times per season. The results demonstrated that biosolids were an appropriate form of fertilizer to maintain turfgrass health when used as a supplement to synthetic fertilizers. The biosolids performed similarly to traditional inorganic fertilizers across multiple health parameters, suggesting they are a viable alternative for sustaining high turf quality.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".