Airborne mapping of sensitive clay—stretching the limits of AEM resolution and accuracy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Due to postglacial uplift, lowlands in Canada, Norway, Sweden and Russia are prone to formation of highly unstable, sensitive, and leached marine clay (quick clay). Quick‐clay failures are dramatic due to its high water content, resulting in liquefaction. It thus poses a major hazard for society and construction projects in particular, and knowledge of its extent is of vital importance. Quick‐clay assessment is usually undertaken in geotechnical boreholes having the disadvantage of giving only information at the borehole location. To overcome this limitation, geophysical ground‐based methods like electrical resistivity tomography have been used successfully. However, when a larger area has to be investigated, electrical resistivity tomography surveys become costly and time consuming. We show results from an airborne electromagnetic survey aiming at detection of different clay units for a road project in southeastern Norway. Airborne electromagnetic data clearly show structures within the sediment layer that correspond well with results from geotechnical boreholes. While a clear distinction between clay and quick clay cannot be derived from airborne electromagnetic alone, our study shows that this method has high‐enough resolution and accuracy to map differences in clay units, which can subsequently be probed at specified locations. Thus, by using airborne electromagnetics to target borehole locations, the costs for the geotechnical drilling program can be reduced significantly.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it