Sample Preparation and Testing Methods for the Evaluation of Microcrystalline Waxes for the Seismic Protection of Art Objects
Bibliographic record
Abstract
Abstract Use of microcrystalline waxes for the protection of ceramic art objects from seismic events is an inexpensive and relatively popular technique. Unfortunately, because of the high porosity of some ceramics and the fragility of their glazes and paints, the surface of many art objects may be vulnerable to damage from the microcrystalline wax. Thus, a conservative application approach is needed—applying only as much as is actually required for predicted levels of ground movement. Determining this quantity and verifying the best application technique (e.g., hot versus cold) has yet to be established. This paper presents the development of testing techniques to optimize the application of microcrystalline waxes; specifically, the pioneering of tensile and shear sample preparation. These procedures were applied to 70 tensile and 175 shear tests on paraffin wax, beeswax, and four microcrystalline waxes. Static testing methods demonstrated the clear superiority of certain products and average performance capabilities of up to 167 kN/m2 in tension and 89 kN/m2 in shear, under light loading.
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 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 | 0.016 | 0.009 |
| 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".