Self Disinfecting Reversible Hydrocolloid Impression Gels: Effect of Composition and Nanosilver on Characteristic Properties and Gelation Temperature
Bibliographic record
Abstract
We have developed a new hydrocolloid impression gel to eliminate disinfection process that caused to inaccuracy in dimensions of final mold. At first, the proper sample has been prepared based on recommended formulation in literature as well as trial and errors via experimental works. Formulations prepared by variation amounts of ingredients and also samples prepared by adding nanosilver as an antibacterial agent. Characteristic properties such as tear strength, gel temperature, compressive strength and elastic recovery of prepared hydrocolloid impression gels have been evaluated. The effect of agar, potassium sulfate and di-sodiumtetraborate (Borax) on characteristic properties has been investigated. In addition, role of nanosilver as an antibacterial which can be eliminate disinfecting process, on final properties of gels has been evaluated this work presents the role of ingredient on properties of self disinfecting agar impression gel.
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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 | 0.000 | 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) | 0.001 | 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 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".