Bibliographic record
Abstract
The interpretation of in-situ geotechnical test data needs a unified approach so that soil parameters are evaluated in a consistent and complementary manner with laboratory re- sults. A common thread in assessing in-situ tests is the focus on the geologic stress history, often expressed by the overconsolidation ratio (OCR). For clays, the OCR can be measured by con- solidation tests on undisturbed samples, yet for sands is rather problematic to address. For 6 clays, a hybrid cavity expansion - critical state model is used to match responses measured CPT, CPTu, and DMT. Specifically, tip stress, sleeve friction, penetration porewater pressures, and flat dilatometer readings are fitted by parametric input of OCR, void ratio, friction angle, rigid- ity index, and compressibility parameters. The undrained shear strength (su) of clays is best han- dled via critical-state concepts. Discussions are included for pressuremeter, vane, and T-bar tests. For sands, select empirical methods derived from laboratory chamber testing on reconsti- tuted clean quartz and siliceous sands are reviewed, specifically for effective friction angle φ', OCR, and K0. In a novel look, a special set of undisturbed (frozen) sand samples from 15 loca- tions in Japan, Canada, Italy, Norway, and China is used to check interrelationships for the fol- lowing in-situ penetration tests: SPT, CPT, and Vs. Stiffness of all soils begins with the small- strain shear modulus (G0 = Gmax = ρT Vs 2 ) that can be used together with strength (su or φ') to evaluate stiffness over a range of strains. Supplementary testing by PMT and/or DMT can pro- vide intermediate stiffnesses for tuning of modulus reduction schemes, as well as independent assessments of K0 and OCR.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".