Bibliographic record
Abstract
Stone is one of the oldest building materials, and its conservation ranks as one of the most challenging in the field. The use of alkoxysilanes in the conservation of stone can be traced as far back as 1861, when A. W. von Hoffman suggested their use for the deteriorating limestone on the Houses of Parliament in London. Alkoxysilane-based formulations have since become the material of choice for the consolidation of stone outdoors. This volume, the first to cover comprehensively alkoxysilanes in stone consolidation, synthesizes the subject's vast and extensive literature, which ranges from production of alkoxysilanes in the nineteenth century to the extensive contributions from sol-gel science in the 1980s and 90s. Included are a historical overview, an annotated bibliography, and discussions of the following topics: the chemistry and physics of alkoxysilanes and their gels; the influence of stone type; commercial and non-commercial formulations; practice; lab and field evaluation of service life; and recent developments. This book is designed for conservators, scientists, and preservation architects in the field of stone conservation and will also serve as an indispensable introduction to the subject for students of art conservation and historic preservation.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".