Investigating the Effect of Soil pH on Sorption of Salinomycin in Clay and Sandy Soils
Bibliographic record
Abstract
Salinomycin is a polyether ionophore that is often used to prevent coccidial infections and promote growth in poultry. A considerable portion of the antibiotic is excreted as the parent chemical, which eventually ends up in agricultural soils. This necessitates researchers conducting sorption-desorption studies to better understand the compound's behaviour in the soil environment. Salinomycin sorption was studied in four agricultural soils, including a clay soil with low organic matter content (LOM), a clay soil with high organic matter content (HOM), a sandy soil with HOM, and a loamy sandy (LOM) soil, at three pH levels: 4, 7, and 9. The batch equilibration approach was used to conduct the desorption investigations. All soils were shown to be severely sorbed by more than 98 percent salinomycin, regardless of soil organic matter level or pH. Salinomycin sorption to the sandy soil increased marginally as the pH decreased, while sorption to the two clay soils increased marginally as the pH increased. Salinomycin desorption in methanol was less than 0.2 percent of the amount administered after 72 hours; whereas, it was greater than 70% with phosphate buffer (pH 7). Salinomycin could offer major threats to both shallow ground water and surface water bodies, because the phosphate buffer would imitate, to some extent, the quality of water flowing through field soils containing various salts.
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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".