Fluoro-Anhydrite Compositions with a Light Filler Based on Expanded Perlite Sand
Bibliographic record
Abstract
Lightweight concrete is widely used in our day as a filling material for sandwich panels in the construction industry.On the other hand, the use of gypsum in this aspect is very limited.Block or panels as partition walls produced by foamed or porous gypsum has not been widely publicised.According to literature, similar types of gypsum panels are produced and used in Israel and the former East Germany.During our literature survey, using polystyrene beads as an aggregate for the production of the gypsum blocks or panels has not been discovered.In this study, we have observed the use and production gypsum composites, using polystyrene beads.Even though it is possible to mix polystyrene beads and gypsum without additives, better results are obtained by wetting the beads using a glue with a polymer base for binding as the mixture become more homogeneous.Production is planned for samples between 200kg/m³ and 800kg/m³ density, among those 500-600 kg/m³ mixtures have been found to be the most economical ones and the cavities filled with gypsum up to the maximum extent.Even though the mechanical strength is not a critical issue for these samples, it is found to be sufficient, in addition good heat insulation and fire retardant properties has been observed.Due to the above mentioned properties, polystyrene aggregated gypsum can be used in precast or cast in situ panels as a filling material.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".