Investigation and geotechnical characterization of Perniö clay, Finland
Bibliographic record
Abstract
Understanding the behavior of soft sensitive clays is a key aspect of geotechnical design, especially in those regions where constructions are planned in marine clay areas. In Finland, one of the major geotechnical issues is the stability and deformation of the railway embankments located on soft soil deposits. The Tampere University of Technology (TUT) and the Finnish Transport Agency (FTA) have been carrying out a research project aiming to a better understanding of strength and deformation properties of Finnish soft clays. As a part of this project, a detailed site investigation was conducted at Perniö site in Western Finland. This paper presents the details of the geotechnical investigation, including field testing, sampling operations, and the laboratory testing program. In particular, an open drive tube sampler with 132 mm diameter, designed at TUT, was used to collect high quality samples. For comparison, samples were also taken using the conventional piston samplers and Sherbrooke Mini-block sampler. Field testing included piezocone, vane shear, and seismic piezocone. Laboratory testing consisted of index, consolidation, triaxial and simple shear tests. A comprehensive study of all these data is presented in a framework to describe Perniö soft clay.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".