Use of CPT and other direct push methods for (hydro-) stratigraphic aquifer characterization — a field study
Bibliographic record
Abstract
Every environmental site investigation aims at delineating near-surface (hydro-) stratigraphic units and their characterization. To determine the type and hydraulic properties of sedimentary deposits, direct push (DP) sensor probes and tools are promising methods and are therefore frequently applied to measure high-resolution vertical profiles of soil properties. Given the variety of these tools, the objective of this paper is to compare selected DP tools for the (hydro-) stratigraphic subsurface characterization in a heterogeneous unconsolidated sedimentary aquifer. An overview of current DP applications is given and selected DP tools were tested for reproducibility, as well as their ability to reflect soil variability and to estimate hydraulic conductivity, K. Although resolution differences exist, all of the applied methods captured the main aquifer structure. Correlations of the DP-based K estimates or proxies with DP slug tests (DPST) show that it is possible to describe the aquifer hydraulic structure on less than a metre scale by combining DPST data and continuous DP measurements. Although correlations are site-specific and appropriate DP tools must be chosen, DP is a reliable and efficient alternative for characterizing even strongly heterogeneous sites with complex sedimentary architectures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".