About the problems of the fixactive/protective products for wall paintings especially on the facades
Bibliographic record
Abstract
The selection of protective coatings for painted facades is a delicate process, primarily due to the vast array of products available on the market. The chosen product must adhere to specific criteria: it should be easy to apply, maintain its protective qualities over the years without undergoing chromatic alterations (such as blackening or yellowing), and be reversible. Since the late 20th century, numerous studies have been conducted by the Istituto Centrale per il Restauro in Rome to ensure that protective agents can last for at least 15 years. The product Paraloid B72 (a copolymer of acrylate and methacrylate of methyl and ethyl) has produced very satisfactory results both aesthetically and mechanically, and its use was successfully confirmed in 1970 for the facades in Feltre. In 2000, under the Leader II project "Redevelopment of Urban Fronts in Feltre," a new analysis campaign by the scientific committee recommended the use of Rhodorsil (silane). However, the degradation of the wall paintings on those facades was severe, rendering them increasingly unreadable. After over 40 years of experience with external and internal wall paintings in the Veneto region, particularly in Feltre, restorations in Armenia were approached using the Samedi methodology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".