Integrated assessment of oil leaking accident site with long-term artificial interference
Bibliographic record
Abstract
This paper provides a case study of an assessment of an oil leaking accident site after long-term artificial interference. A cost-effective, rapid and quantitative assessment was carried out in the following order: site hydrogeology study, joint on-site geophysical prospecting (high-density electrical method and ground-penetrating radar method), borehole investigation, sample testing and integrated assessment. The results indicate that oil plumes have been transported from the leak spot to the downstream area, suggesting that surface artificial rainfall is helpful in driving the crude oil plumes. Aquifer heterogeneity dominates the behaviours of the plume movement at site scale. Two residual oil plumes were confirmed, with an estimated total volume of 325·6 m3 for the contaminated soil and groundwater. At last, a site-specific joint leaching, pumping and treating method is proposed for the clean-up of the residual crude oil. This study is provided for a precise assessment prior to remediation.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".