Monitoring Lateral Transport of Ethanol and Dissolved Gasoline Compounds in the Capillary Fringe
Bibliographic record
Abstract
Fuel mixtures composed of gasoline and ethanol are lighter than water and, if enough volume is released into the unsaturated zone, they accumulate in the capillary fringe, acting as a source for dissolved plumes. To evaluate different sampling techniques and transport in the capillary fringe, two controlled releases of gasoline and ethanol mixtures were conducted in the unsaturated zone at the CFB Borden aquifer. Lateral flow and transport in the capillary fringe is well documented, but this is the first field documentation of transport of organic compounds in the capillary fringe following fuel spills. Transport of both ethanol and hydrocarbon compounds in the capillary fringe was significant, ethanol being transported exclusively above the water table. Significant concentrations of benzene were found above the water table up to 6 m downgradient from the source. The groundwater sampling techniques evaluated were fully screened monitoring wells; multilevel wells constructed with ceramic porous cups located in both the capillary fringe and below the water table; and soil coring. The fully screened monitoring well was unable to draw water from the capillary fringe and so failed to adequately describe the contaminant distribution. Pore water concentrations obtained by sampling the multilevel porous cups and calculated based on analysis of soil core yielded similar results.
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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".