Bibliographic record
Abstract
【Ethanol washing with distillation as a cleanup process of polycyclic aromatic hydrocarbon(PAH)-contaminated soil was investigated in this study. A multistage ethanol washing with distillation process was applied to three different types of soil, i.e., sandy soil, alluvial soil, and clay with the initial concentration of benzo(a)pyrene 10 mg/kg, benz(a)anthracene 250 mg/kg, and pyrene 100 mg/kg soil. Ethanol was selected as washing solvent because of its high PAH removal efficiency, low cost, and non-toxicity comparing to the other solvent such as isopropyl alcohol and sodium dodecyl sulfate. The satisfactory results (i.e. lower than benzo(a)pyrene 1 mg/kg, pyrene 10 mg/kg, benz(a)anthracene 25 mg/kg, which are the Canada or the Netherlands soil standard) for three types of soils were obtained by at most five-six times washing. It was suggested that organic content in soil decreased the removal efficiency by ethanol washing.】
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".