Fresh and Composted Paper Sludges Sustain Soil Productivity
Bibliographic record
Abstract
In this 5-yr study, application frequency of fresh (FDS) and composted (CDS) paper sludges was evaluated on soil properties and silage corn (Zea maysL.) and barley (Hordeum vulgareL.) yields and N uptake by comparing one application (2000) with repeated applications (2000, 2001, 2002). Treatments consisted of a control with neither amendment nor N fertilizer, a recommended N rate for corn (160 kg N ha−1) and barley (90 kg N ha−1), and FDS and CDS at a rate of 40 Mg ha−1on wet basis with or without reduced N fertilizer (120 kg N ha−1) on corn. Compared to the control, the FDS or CDS applications significantly increased the proportions of soil larger macroaggregates (>2 mm) and the mean-weight diameter (MWD) of aggregates, regardless their application frequency. Single or three yrs additions of FDS or CDS produced, on average, an increase of 25 to 31% of the soil C and N contents compared to the control and the recommended N fertilizer treatment (160 kg N ha−1). In the first year of their application, the FDS or CDS with or without supplemental N fertilizer (120 kg N ha−1) reduced silage corn and N uptake, compared to the control probably due to N immobilization. However, silage corn yields were increased in the following years with one application or with repeated application of FDS or CDS. Results show that benefits on soil properties and crop yields of single application of FDS and CDS were similar to those of the triple applications and were still noticeable a few years following the last application.
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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".