Field comparison of the point velocity probe with other groundwater velocity measurement methods
Bibliographic record
Abstract
Field testing of a new tool for measuring groundwater velocities at the centimeter scale, the point velocity probe (PVP), was undertaken at Canadian Forces Base, Borden, Ontario, Canada. The measurements were performed in a sheet pile‐bounded alleyway in which bulk flow rate and direction could be controlled. PVP velocities were compared with those estimated from bulk flow, a Geoflo® instrument, borehole dilution, colloidal borescope measurements, and a forced gradient tracer test. In addition, the velocity profiles were compared with vertical variations in hydraulic conductivity (K) measured by permeameter testing of core samples and in situ high‐resolution slug tests. There was qualitative agreement between the trends in velocity and K among all the various methods. The PVP and Geoflo® meter tests returned average velocity magnitudes of 30.2 ± 7.7 to 34.7 ± 13.1 cm/d (depending on prior knowledge of flow direction in PVP tests) and 36.5 ± 10.6, respectively, which were near the estimated bulk velocity (20 cm/d). The other direct velocity measurement techniques yielded velocity estimates 5 to 12 times the bulk velocity. Best results with the PVP instrument were obtained by jetting the instrument into place, though this method may have introduced a slight positive bias to the measured velocities. The individual estimates of point velocity direction varied, but the average of the point velocity directions agreed quite well with the expected bulk flow direction. It was concluded that the PVP method is a viable technique for use in the field, where high‐resolution velocity data are required.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".