Microstructure and cementation of two carbonatic fine-grained soils
Bibliographic record
Abstract
This paper presents an investigation of the microstructure and cementation of two carbonatic fine-grained soils obtained from a deposit of lacustrine origin formed during the Wisconsin glaciation. The two soils differ in the degree of cementation (with average total carbonate contents of ∼55% and ∼38%), the dominating carbonate mineral (calcite versus dolomite), and the forms of carbonates present. The study is founded on observations of the microstructure using scanning electron microscopy (SEM) equipped with energy-dispersive X-ray (EDX) spectrometry, and examination of the effects of carbonate dissolution on Atterberg limits and particle-size distribution. In both soils, the majority of the carbonate is in the form of a coating layer on the clay and silt particles, with a thickness less than 2–3 μm, and decreasing in the sample with lower carbonate content. This coating layer “networks” particles and groups of particles. Carbonate cementation impacts the engineering properties of both soils, and the site’s overconsolidation ratio (OCR) profile clearly reflects changes in carbonate content and microstructure. One-dimensional compression tests show that cementation is associated with a moderate degree of structuring, and that the resulting structure is stable, with no complete destructuration occurring even after the effective stress exceeds 10 times the preconsolidation stress.
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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 | 0.001 | 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".