Destruction of DNAPL through a Green Technology—TCE Source Area Bioremediation
Bibliographic record
Abstract
A single-injection of a proprietary electron donor additive remediated a trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) source, reducing TCE concentrations by 99.99 percent in less than 9 years. The remedial program achieved the enhanced reductive dechlorination (ERD) of chlorinated volatile organic compounds (cVOCs) within an overburden groundwater source area at a site located in central New Hampshire, USA. The baseline TCE concentration was 97,400 micrograms per liter (μg/L) in September 2001 and decreased to less than 10 μg/L by May 2010. This green technology destroyed the DNAPL and has shown great promise at other cVOC-impacted sites for both full-scale and Proof-of-Concept remedial programs. The Proof-of-Concept test, which is discussed at the end of the paper, is an economical means to evaluate feasibility and advance a site toward cost-effective full-scale 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 | 0.000 | 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) | 0.001 | 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".