Application of passive soil gas technology to determine the source and extent of a PCE groundwater plume in an urban environment
Bibliographic record
Abstract
Abstract In situations where groundwater supplies have been impacted by volatile organic compounds (VOCs), such as tetrachloroethene (PCE), and the source has not been identified, the costs to identify the source and plume migration patterns may be extremely high. The costs for an investigation increase with the number and depth of borings and the number of samples that are collected and analyzed. An environmental investigator and the Arizona Department of Environmental Quality (ADEQ) have successfully utilized passive soil gas (PSG) surveys in Arizona to cost‐effectively investigate VOC impacts to groundwater and identify potential sources of impact. PSG surveys are minimally intrusive, and more samples can be collected for the same cost when compared to active soil gas surveys and conventional soil and groundwater sampling programs. The result is a surficial representation of the contaminant plume and the location of “hot spots,'' which are the potential sources. This provides a better understanding of the nature and extent of the impact and allows for a focused subsurface investigation, which subsequently reduces drilling and sampling costs. © 2008 Wiley Periodicals, Inc.
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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) | 0.000 | 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) | 0.000 | 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".