Reliability evaluation of shallow foundation bearing capacity on<i>c</i>' ϕ' soils
Bibliographic record
Abstract
As our understanding of soils has been steadily improving, the characteristics of its variability can now be highlighted. This has practically changed our geotechnical modus operandi from strictly deterministic models to semiprobabilistic or even strictly probabilistic models. The latter are still to be regarded as experimental and cannot, for the time being, be used routinely in practical working applications. However, the ongoing, continued research and study of these methods combine to develop their worth and bring out any drawbacks. This paper proposes a possible application of probabilistic methods to the study of shallow foundations reliability with respect to their bearing capacity. The study concerns a foundation on a soil characterized by effective cohesion c' and friction angle ϕ', considering possible values of correlation coefficients between them and taking into account the effects of vertical fluctuation scale. The results show that higher reliability indexes are found when correlations between c' and ϕ' are negative and when the fluctuation scale has a minimum value.Key words: reliability, bearing capacity, shallow foundations, friction angle, cohesion.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".