Field Demonstration and Validation of a New Device for Measuring Water and Solute Fluxes
Bibliographic record
Abstract
Abstract : The Department of Defense (DoD) has a critical need for technologies that provide cost-effective long-term monitoring of volatile organic chemicals, petroleum and related compounds, trace metals, and explosives. In recent years, the utility of contaminant flux and contaminant mass discharge as robust metrics for assessing site risks and site remediation performance has gained increasing acceptance within scientific, regulatory, and end-user communities. The passive flux meter (PFM) is a new technology that measures subsurface water and contaminant flux directly. This technology addresses the DoD need for cost-effective, long-term monitoring because flux measurements can be used for process control, remedial action performance assessments, and compliance monitoring. Under the Environmental Security Technology Certification Program (ESTCP) Project No. ER- 0114, the PFM was demonstrated and validated as an innovative flux monitoring technology at several locations, including the National Air and Space Administration s (NASA) Launch Complex 34 (LC-34) in Cape Canaveral, Florida; the Canadian Forces Base in Ontario, Canada (Borden); the Naval Construction Base in Port Hueneme, California; and the Naval Surface Warfare Center at Indian Head, Maryland. Projects at NASA, Borden, and Port Hueneme included objectives of evaluating the flux meter as a technology for direct in situ measurement of cumulative water discharge and contaminant flux under controlled flow and under natural gradient conditions. Tetrachloroethene (PCE), trichloroethene (TCE), dichloroethene (DCE), vinyl chloride, ethylene, and methyl tertiary butyl ether (MTBE) were the contaminants studied. At the Naval Surface Warfare Center at Indian Head, Maryland, the PFM was demonstrated and validated as a technology for measuring water and perchlorate fluxes. Data and results from all sites were compiled and interpreted to expedite regulatory and end-user acceptance and to stimulate commercialization.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".