Ion availabilities in two forest soils amended with alkaline-treated biosolids, agricultural lime, and wood fly ash over a 10-week period
Bibliographic record
Abstract
Two forest soil B-horizons were amended with alkaline-treated biosolids (ATB), powdered agricultural lime, and wood fly ash under controlled conditions to compare initial ion availabilities over a 10-week period. ATB was most effective in supplying available Ca2+ but least effective in supplying available Mg2+, for which lime was most effective. Availability of K+ and SO42–-S was greatest in fly ash amended soils because of high K and S loading rates and the high electrical conductivity of this amendment. Mineral N (NO3–-N + NH4+-N) availability increased in ATB amended soils, stayed the same in lime amended soils, and decreased in fly ash amended soils. Availability of PO43–-P was low in all soils but slightly enhanced in ATB amended soils. Fluxes of Cu2+, Pb2+, Zn2+, and Mn2+ in amended soils generally decreased over time in association with increased soil pH. Fluxes of Cd2+ were not affected by any treatment. Results suggest that ATB is equally as effective as or more effective than lime and fly ash at immediately supplying Ca2+, but less effective at supplying Mg2+ because of low inputs and cation competition. This suggests that ATB amendments could be an alternative means of quickly adding available Ca2+ to Ca-depleted forest soils as long as potential impacts on other nutrient base cations are considered.
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
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".