Effect of municipal and pulp mill effluents on the chemical properties and nutrient status of a coarse-textured Brunisol in a growth chamber
Bibliographic record
Abstract
Maximizing productive use and minimizing the environmental impacts of effluents require research on application rates. This study evaluated the effect of effluents from a Kraft pulp mill [a final effluent (KPME) and a waste activated sludge (WAS)], a municipality (ME) and tap water (TPW) applied at rates of 1.5, 3 and 6 mm d-1 on reed canarygrass (Phalaris arundinacea L. cv. Vantage) and hybrid poplar (Populus deltoides × P. petrowskyana var. Walker). The two pulp mill effluents significantly increased soluble soil SO4, Na and Cl. Soil solution electrical conductivity (EC) and sodium adsorption ratio (SAR) increased with pulp mill effluents compared with ME and TPW. Soil solution SAR increased from less than 1 to a range of 2.7 to 4.0 for the municipal effluent and 8.4 to 14.0 for the two pulp mill effluents. Soil solution EC increased from 1.1 to 2.3 dS m-1 to a range of 1.8 to 3.4 dS m-1 for municipal effluent and 5.1 to 6.1 dS m-1 as a result of pulp mill effluent applications. Under reed canarygrass, soils had lower concentrations of cations and anions than those under hybrid poplar, suggesting crop uptake and leaching. Thus, salt loadings of soils must be considered when determining application rates of effluents for irrigation. Key words: Electrical conductivity, hybrid poplar, effluent irrigation, sodium adsorption ratio
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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) | 0.001 | 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 | 0.001 |
| 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".