Statistical analysis based geotechnical characterization of Kathmandu soils
Bibliographic record
Abstract
Kathmandu Valley, the capital of Nepal, is a highly populated and rapidly urbanised area of the country built upon lacustrine and fluvial origin deposits. Because the valley deposit is located in an earthquake-prone zone with a long history of catastrophic earthquakes, it is vulnerable to numerous geohazards like liquefaction. Although a few localized geotechnical studies have been conducted in the valley, holistic understanding, modelling, and geotechnical soil characterisation are seldom documented. This study attempts to characterize the Kathmandu soil based on geotechnical properties using statistical analysis approach. We have collected and analysed more than 400 geotechnical investigation reports and bored 10 test locations. Statistical analysis and representation of index properties, consolidation parameters, shear strength, SPT-N value, and shear wave velocity have been assessed in this paper. These findings can aid structural and foundation engineers in studying foundations, cost estimation of geotechnical investigations, and planning and implementing various civil engineering projects.
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How this classification was reachedexpand
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) | 0.014 | 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 teacher head, 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".