Enhanced migration of polychlorodibenzo-<i>p</i>-dioxins and furans in the presence of pentachlorophenol-treated oil in soil around utility poles: Screening model validation
Bibliographic record
Abstract
Field samples were collected around six pentachlorophenol (PCP)-treated wooden poles (in clay, organic soil, and sand) to evaluate the vertical migration of polychlorodibenzo-p-dioxins and furans (PCDD/Fs). Soils were characterized, PCDD/Fs, C(10)-C(50), and PCP were analyzed for seven composite samples located at a depth from 0 to 100 cm and at a distance from 0 to 50 cm from each pole. Concentrations of PCDD/Fs measured in organic soils were the highest (maximum 1.2E + 05 pg toxic equivalent TEQ/g soil), followed by clay (maximum 3.8E + 04 pg TEQ/g soil) and sand (maximum 1.8E + 04 pg TEQ/g soil). Model predictions, including the influence of wood treatment oil, were validated using measured concentration values in soils around poles. The model predicts a migration of PCDD/Fs due to the migration of oil, which differs depending on the type of soil: in clay, 90% of PCDD/Fs are predicted to remain in the first 29 cm, whereas in sand, 80 to 90% of the emitted PCDD/Fs are predicted to migrate deeper than 185 cm. For the organic soil, the predicted migration depth varies from 90 to 155 cm. This screening model allows evaluating the danger of microcontaminated sites around PCP-treated wooden poles: from a risk assessment perspective, in the case of organic soil and clay, no PCDD/F contamination is to be expected below the pole, but high levels of PCDD/Fs can be found in the first 2 m below the surface. For sand, however, significantly lower levels of PCDD/Fs were predicted in the surface soil, while the migration depth remains elevated, posing an inherent danger of aquifer contamination under the pole.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".