Remediating TCE‐contaminated groundwater in low‐permeability media using hydraulic fracturing to emplace zero‐valent iron/organic carbon amendment
Bibliographic record
Abstract
Abstract A field pilot test in which hydraulic fracturing was used to emplace granular remediation amendment (a mixture of zero‐valent iron [ZVI] and organic carbon) into fine‐grained sandstone to remediate dissolved trichloroethene (TCE)‐contaminated groundwater was performed at a former intercontinental ballistic missile site in Colorado. Hydraulic fracturing was used to enhance the permeability of the aquifer with concurrent emplacement of amendment that facilitates TCE degradation. Geophysical monitoring and inverse modeling show that the network of amendment‐filled fractures extends throughout the aquifer volume targeted in the pilot test zone. Two years of subsequent groundwater monitoring demonstrate that amendment addition resulted in development of geochemical conditions favorable to both abiotic and biological TCE degradation, that TCE concentrations were substantially reduced (i.e., greater than 90 percent reduction in TCE mass), and that the primary degradation processes are likely abiotic. The pilot‐test data aided in re‐evaluating the conceptual site model and in designing the full‐scale remedy to address a larger portion of the TCE‐contaminated groundwater plume. © 2012 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".