Estimating Groundwater and 1,4-dioxane Contaminant Mass Flux in a Karst Aquifer using the Discrete Fracture Network - Matrix Field Approach
Bibliographic record
Abstract
1,4-dioxane was detected in a municipal supply well in the karstic Upper Floridan Aquifer. High aquifer transmissivity and site dimensions create uncertainty in hydraulic gradients, reducing confidence in Darcy’s law-based mass flux calculations. Depth-discrete, high-resolution rock core contaminant profiles and borehole geophysical logs were collected to assess contaminant mass storage in the matrix and proximity to fractures. Hydraulically active features were identified under natural hydraulic conditions using active distributed temperature sensing in FLUTe™ lined boreholes. Modified passive flux meters and pressure/temperature transducers were deployed in depth-discrete zones (1-2 m long) external to the FLUTe™ liner to quantify water flux, contaminant flux, and characterize site hydraulics. PFMs deployed behind FLUTe™ liners are effective in this field setting enabling quantification of groundwater specific discharge and mass flux despite low hydraulic gradients. Rock core matrix concentrations range higher and lower than groundwater concentrations suggesting 1,4-dioxane matrix diffusion is a key process onsite.
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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 | 0.001 | 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".