Enantioselective Degradation of Organochlorine Pesticides in Background Soils: Variability in Field and Laboratory Studies
Bibliographic record
Abstract
Variability in the enantioselective degradation of chiral organochlorine pesticides (alpha-HCH, cis- and trans-chlordane (CC and TC), and o,p'-DDT) in the field and laboratory was investigated. Background soils presumably receive the same EF signature of a compound via atmospheric deposition and then degrade that compound in a way that can vary over small spatial areas. Background soils from woodland and grassland areas were sampled to compare chiral signatures and determine the spatial variability within a few square meters. The enantiomer fractions, EF = areas of the (+)/[(+)+(-)]-enantiomers, showed variability between and within ecosystems. For example, the EF of CC varied between 0.272 -and 0.558 in nine samples taken over a few square meters, and a range of 0.431-0.506 was found within depths of a few centimeters. Woodland and grassland soils were spiked with alpha-HCH, TC, CC, and o,p'-DDT, and one portion was placed in the field to monitor changes in EF under in situ conditions and the other taken to the laboratory. In general, the enantiomer degradation preferences in the laboratory paralleled those in the field, with some differences. Soil organic matter content and pH exerted a minor influence on this variability. The results of this study have implications for the use of chiral compounds to make inferences about air-soil exchange and for the mechanisms of biodegradation/ biotransformation of anthropogenic compounds in soils.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".