Effects of Treated Municipal Wastewater on Soil Chemical Properties and Heavy Metal Uptake by Sorghum (sorghum bicolor L.)
Bibliographic record
Abstract
In order to investigate the effect of treated municipal wastewater on soil chemical properties and heavy metal uptake by sorghum an experiment was carried out in the Institute of Agriculture at Zabol University, Iran 2007 in a randomized complete block design with four replications. The treatments were managed for irrigation; with well water during entire period of growing season as control (T1); wastewater during the first half of growing season (T2); wastewater during the second half of growing season (T3); wastewater and well water alternately (T4) and wastewater during entire period of growing season (T5). The results have indicated that irrigation with wastewater lead to significant increase in N, P, K, Ca, Na, Mg, SAR, EC, O.C% than control treatment (p ? 0.05). In addition, the increases of Zn, Fe, Mo in soil, and Cu, Fe in sorghum plant were statistically significant in comparison with control treatment (p?0.01). The highest transfer coefficient was observed for Mo and Pb (1.28, 1.02), and the lowest for Cu (0.077 which highlight the high absorption power of sorghum toward these elements.
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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) | 0.001 | 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".