Coupling Leaching-Bioremediation for Petroleum-Contaminated Soil
Bibliographic record
Abstract
Petroleum-contaminated soils are difficult to remediate due to a wide range of point/nonpoint sources of pollution and complex components.Here, the optimizations of the leaching process and process parameters were carried out based on the selection of conventional eluting agents and the development of oligomers, modified bio-based surfactants and synergists.Furthermore, a new and efficient leaching system was constructed.Moreover, based on the characteristics of the soil after leaching and its flora structure, the best degradation flora was selected and optimized.The proposed leaching-bioremediation coupling treatment process could make the petroleum hydrocarbon content of the contaminated soil less than 0.45%.The field validation was also conducted for petroleum hydrocarbon-contaminated soil with a mass of 12 000 t. Finally, the economic and environmentally friendly remediation technology and process for oil-contaminated soil are established.This approach can provide technical support for the environmental protection of sudden oil pollution and other historical problems in oil areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".