Mapping quick clay using airborne resistivity measurements
Bibliographic record
Abstract
Purpose: One of the major soil problems that the construction industry may face is the presence of a certain type of highly sensitive marine clay, known as quick clay. The quick clay possesses properties that allow the clay to move from being relatively stable to on mechanical impact losing virtually all shear strength and act as a viscous mass. The majority of the Swedish, Norwegian and Canadian landslides, caused by quick clay, have caused significant consequences due to lack of bearing capacity of quick clay. In order to prevent these landslides knowledge about where there is quick clay is required. A large-scale mapping work has therefore been ongoing for a long time. The government has for some time been researching how to streamline mapping work and the result has shown a connection between quick clay attendance and increased resistivity. The purpose of this study is to develop a theoretical framework for areas with higher risk for presence of quick clay based on linking the resistivity to geotechnical properties. Method: The study has mainly applied quantitative data collection methods in the form of data analyzes combined with literature studies. Measurement data used in the study comprise of data collected through geotechnical and geophysical surveys. Literature studies have mainly been supported by reports from previous research in the field. Result: The result of the study points to a variety of geological factors that can give rise to increased risk of quick clay existence such as good permeability, artesian groundwater and uneven mountain subsidence etc. The study also shows a possible link between resistivity and sensitivity. Consequences: The study demonstrates the possibility of linking resistivity to the geotechnical property sensitivity to facilitate and streamline the mapping of quick clay through airborne resistivity measuring. Limitations: The study is limited to studying two research areas in south western Sweden, Strömstad and Lödöse. The study intends to examine the evidence from previous surveys and no further supplementary studies are conducted. The work is also delimited to study the geotechnical and geophysical properties of quick clay (in terms of resistivity). Chemical aspects are not taken into account.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".