Study on Serpentinites and the Consequence of the Misuse of Natural Stone in Buildings for Construction.
Bibliographic record
Abstract
Some rocks are very attractive as ornamental stone, but not all of them accomplish the needed requirements to be used in construction. Serpentinite can be an appealing rock, very commonly used as dimension stone. However, not all serpentinites can be used in such a way. The most widely used commercial serpentinite comes from Pakistan and India (i.e., Rajasthan Green), but other countries also produce serpentinites, such as Italy (Verde Alpi, Verde Polcevera, Verde Prato), United States (Vermont Verde Antique), and Spain (Verde Macael, Verde Pirineos). The geomechanical properties of a serpentinite are strongly related to its mineralogy (serpentine-group minerals and carbonates, mostly), and not all serpentinites are created equal. We have compared the mineralogy and mechanical properties of serpentinites that comply with the Standard Specification for Serpentinite as Dimension Stone (i.e., Rajasthan Green, Verde Macael) with those that do not (Verde Pirineos). Verde Pirineos consists of lizardite, and the carbonates, mostly dolomite, are restricted to veins. Rajasthan Green consists of antigorite, and most of the serpentine has been replaced by carbonates, dominantly magnesian calcite. Taking into account their composition and textures, rocks with such differences will evolve in different ways in a weathering environment. In replacing damaged serpentinite from a building, it is important that the new piece have the same characteristics, otherwise the replaced tiles will not look appropriate in aesthetic terms. This is particularly important in restoring monuments. Petrographic studies and x-ray diffraction are essential in analyzing the commercial potential of these rocks, and results are directly related to the geomechanical behavior of the samples. Knowledge of these characteristics would help to choose the right replacement in case of restoration of monuments and other buildings.
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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 | 0.001 | 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) | 0.000 | 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 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".