Relationship between electrical resistivity and basic geotechnical parameters for marine clays
Bibliographic record
Abstract
Recently, considerable efforts have been made in the attempt to map quick clay areas using electrical resistivity measurements. However there is a lack of understanding regarding which soil parameters control the measured resistivity values. To address this issue, inverted resistivity values from 15 marine clay sites in Norway have been compared with basic geotechnical index properties. It was found that the resistivity value is strongly controlled by the salt content of the pore fluid. Resistivity decreases rapidly with increasing salt content. There is also a relatively clear trend of decreasing resistivity with increasing clay content and plasticity index. Resistivity values become very low (≈5 Ω·m) for high clay content (>50%), medium- to high-plasticity (Ip ≈ 20%) materials with salt content values greater than about 8 g/L (or corresponding remoulded shear strength values greater than 4 kPa). For the range of values studied, there is poor correlation between resistivity and bulk density and between resistivity and water content. The data studied suggest that the range of resistivity values corresponding to quick clay is 10 to 100 Ω·m, which is consistent with other published limits. A comparison is made between two-dimensional electrical resistivity tomography (ERT) and resistivity cone penetration test (RCPTU) data for two of the sites and the two sets of data show similar trends and values irrespective of scale effect.
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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 | 0.002 |
| 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) | 0.001 | 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".