Soil and Plant Response to MSW Compost Applications on Lowbush Blueberry Fields in 2000 and 2001
Bibliographic record
Abstract
SUMMARY Field experiments were initiated in May 1999 to investigate the application of municipal solid waste (MSW) compost to low-bush blueberry (Vaccinium angustifolium Ait.) fields. Three sites were selected: Debert, NS (Truro sandy loam) and two sites near Musquodoboit, NS (both Rawdon gravely loamy sands). Treatments at each site consisted of a randomized complete block design with six treatments (Control [no fertilizer], NK fertilizer, NPK fertilizer, and three rates of MSW compost) blocked four times. Compost treatments provided the equivalent of 100, 200, and 400 kg ha−1 of total N, respectively. The experimental objectives were to evaluate soil and plant response to the compost and to determine whether the organic amendment could be used as an alternative to chemical fertilizers. Yield, soil fertility, and plant nutrients were evaluated in blueberry leaf tissue and fruit over two years. The MSW compost had a strong (K) and a mild effect (P, Ca, Mg, S, Cu, Zn) on extractable soil nutrients, while a strong effect (Mn) and a mild effect (N, K) was observed on leaf tissue nutrients. The fruit yield was not affected by the treatments. Therefore, the compost treatments provided equivalent amounts of plant essential nutrients without negatively influencing trace element absorption.
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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".