Sorption and Desorption of Three Endocrine Disrupters in Soils
Bibliographic record
Abstract
Sorption of the estrogens estrone (E1), 17beta-estradiol (E2) and 17alpha-ethynylestradiol (EE2) on four soils was examined using batch equilibrium experiments with initial estrogen concentrations ranging from 10 to 1000 ng mL-1. At all concentrations, >85% of the three estrogens sorbed rapidly to a sandy soil. E1 sorbed more strongly to soil than E2 or EE2. Partial oxidation of E2 to E1 was observed in the presence of soils. Autoclaving was more effective at reducing this conversion than inhibition with sodium azide or mercuric chloride, and had little effect on sorption, relative to the chemical microbial inhibitors. Sorption of EE2 was greater for fine-textured than coarse-textured soils, but greater than 90% of EE2 sorbed onto all four soils. The greatest degree of desorption of estrogens from the sandy soil occurred with the lowest initial concentration of 10 ng mL-1 and reached levels >or=80% for E1 and E2. Desorption of EE2 was greater in coarser textured soils than finer-textured soils. Again, relative desorption from all soils was greatest with low initial concentrations. Therefore, at environmentally relevant concentrations, estrogens quickly sorb to soils, and soils have a large capacity to bind estrogens, but these endocrine-disrupting compounds can become easily desorbed and released into the aqueous phase.
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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".