Heritage Stone 3. Degradation Patterns of Stone Used in Historic Buildings in Brazil
Bibliographic record
Abstract
Brazil’s heritage buildings were built using different types of natural stone, including sandstone, limestone, quartzite, granite, gneiss, steatite (soapstone) and schist. Historic buildings are located in cities such as Recife, Olinda, Salvador, Rio de Janeiro, Congonhas and Ouro Preto; some are over 300 years old. They show evidence of different alteration and decay processes, with the latter leading to a loss of value because of physical and chemical modifications in intrinsic properties of the natural stones used. Consequently, these buildings function as open-air laboratories, and contribute to the study of deterioration in such monuments. On going investigation of alteration and decay reveals that they are affected by a diverse group of processes that are, in part, influenced by lithological factors. This understanding will contribute to the choice of preservation methods that will be applied in order to arrest degradation.RÉSUMÉLes édifices classés brésiliens ont été batis en roches variées. On a employé des grès, des calcaires, quartzites, granites, gneiss, ainsi que la stéatite et des schistes. Les bâtiments historiques, dont certains ont plus de 300 ans, se trouvent dans des villes comme Recife, Olinda, Salvador, Rio de Janeiro, Congonhas et Ouro Preto. Ils présentent les marques de différents processus d'altération et de deterioration, ce dernier conduisant à une perte de valeur, en raison de modifications physiques et chimiques dans les propriétés intrinsèques des pierres naturelles utilisées. De la sorte, ces bâtiments fonctionnent comme des laboratoires à ciel ouvert et contribuent à l’étude des modalités de dégradation des monuments. L’étude en cours des phénomènes d’altération et de décomposition révèle la diversité des processus en cours et leur relation avec la lithologie. La reconnaissance de ces phénomènes aidera à choisir les méthodes de conservation destinées à bloquer la dégradation.
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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 | 0.000 | 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".