Measurement of groundwater and contaminant fluxes using a combined system of fractured rock passive flux meter and multiport sampler
Bibliographic record
Abstract
Groundwater and contaminant movement in fractured rock aquifers is highly variable and its dependence on fracture aperture, orientation and network interconnectivity is not well understood. This poses a challenge on the measurement of groundwater and contaminant fluxes, especially using open-hole techniques, which significantly alter natural flow conditions by connecting different fractures along an open borehole or a well. The Fractured Rock Passive Flux Meter (FRPFM) is a closed-hole device for measuring water and contaminant fluxes at individual fractures. Here we present an improved FRPFM that is combined with the G 360 MultiPort System (G 360 MPS), and perform laboratory tests to measure water and contaminant fluxes at inclined and perpendicular fractures of different apertures. Results showed that water and contaminant fluxes were measured with relative errors of ±25 % and ± 14 %, respectively. The results also showed that the selection of appropriate Activated Carbon Felt can improve the accuracy of water flux measurements, and the fraction of tracer remaining on the felt in each experiment exhibited the expected breakthrough curve behaviour. Water flux was measured correctly up to 50 % of tracer loss, but beyond this point, the measurements became less accurate as tracer displacement rate declined.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".