Spatial distributions of perchloroethylene reactive transport parameters in the Borden Aquifer
Bibliographic record
Abstract
We determined the descriptive statistical and spatial geostatistical properties of the perchloroethene ln Kd and the ln k of a 1.5 m thick by 10 m horizontal transect of the Borden aquifer near the location of the Stanford‐Waterloo (SW) tracer experiment. The ln Kd distribution is not normal and is right skewed because of a few high values that occur localized in two regions of the transect. In contrast, the ln k data can be characterized by a normal distribution. A linear regression of ln Kd on ln k yields a statistically significant positive correlation, also shown at small lags in the cross correlogram. No significant vertical or horizontal trend in the ln Kd data was detected. The semivariogram ranges of ln k and ln Kd differ from one another in the vertical direction (0.33 ± 0.06 m and 0.20 ± 0.04 m, respectively) and are much less than the horizontal ranges (a few meters). Despite significant effort the horizontal range of ln Kd remains poorly characterized because of limitations of the sample locations. Many of the characteristics described above do not match those assumed in prior theoretical studies that examined the importance of various aquifer characteristics on SW tracer transport. We suggest that there is knowledge to be gained by revisiting the conclusions of these prior studies in light of the new information presented here.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".