Evaluation of the status of contamination of arable soils in Poland with DDT and HCH residues; national and regional scales
Bibliographic record
Abstract
The aim of our study was to evaluate the content of organochlorine pesticides (DDTs and HCHs) in the upper layer of arable soils in Poland. 214 soil samples were analyzed for the content of three HCH congeners (α-HCH, β-HCH, and γ-HCH) and three DDT compounds (pp’DDT, pp’DDE, and pp’DDD). The median soil concentration of Σ3DDT was 24.39 µg·kg -1 , while for Σ3HCH it was 2.85 µg·kg -1 with the highest contribution of γ-HCH isomer. Polish criteria for agricultural soils not polluted with DDTs are met by half of the samples. In the case of γ-HCH the Polish limit value of 0.5 µg·kg -1 was met in 6.5% of the samples. However, according to the less restrictive systems applied in other countries (Canada, Romania) none of the soil samples create a hazard due to contamination with DDTs, and only 6-11% exhibit too high concentrations of γHCH (residues of Lindane). The mean contents of DDTs and γ-HCH in soils from different provinces varied widely with the reverse interdependence of both groups of pesticides. The districts with the highest concentrations of DDT (Podlaskie, Wielkopolskie, and Mazowieckie) were characterized by the lowest mean residues of Lindane. This suggests the long-term effects of the prescriptive state system of distribution of pesticides used in Poland more than 40 years ago.
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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 | 0.001 |
| 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 | 0.001 |
| 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".