Application of passive soil gas technology to determine the source and extent of a PCE groundwater plume in an urban environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 |
| 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 it