Soil phosphorus fractions following annual paper mill biosolids and liming materials application
Bibliographic record
Abstract
Industrial by-products such as paper mill biosolids (PB) and different liming materials have been used as fertilizers and amendments in agricultural soils for many decades. However, little is known about the effects of their repeated application on soil nutrient availability, particularly phosphorus (P). A 6-yr field study (2000-2005) was conducted in the province of Quebec to investigate the effect of repeated annual applications of different PB and industrial by-products on selected soil chemical properties, especially soil P fractions. Different PB rates (0 to 90 Mg wet ha-1) and several liming products (lime mud, wood ash, calcitic lime, and Mg by-products) were annually applied to field crops after seeding. Soils were sampled before seeding in May 2003 and at harvest in October 2005. Results showed that HCl-P was the largest P pool, accounting for about 64% of the total P fraction, and that the repeated applications of liming products significantly increased this pool and decreased the organic P pools. The NaOH-Po and residual-P were significantly lower in 2005 than in 2003, indicating that PB application without supplemental P fertilizer inputs enhanced the mobility and/or mineralization of NaOH-Po and the transformation of recalcitrant P to more labile forms with time. Lime mud (LM) was found to be the best liming material owing to its high neutralization capacity and positive effect on soil P availability over time. Key words: Paper mill biosolids, alkaline residuals, lime, wood ash, soil P fractions
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".