The Effects of Disinfectants on Dimensional Accuracy and Surface Quality of Impression Materials and Gypsum Casts
Bibliographic record
Abstract
BACKGROUND: The study aimed to evaluating the effect of disinfecting impression materials on the dimensional accuracy and surface quality of the resulting casts. METHODS: Impressions of a steel die constructed according to ANSI/ADA specification No.18 were made with each of alginate, addition cured silicone, condensation cured silicone and zinc oxide eugenol paste, and disinfected consequently by each of 0.2% chlorhexidine gluconate, 1% sodium hypochlorite, 2% gluteraldehyde for 5 minutes, and 0.5% sodium hypochlorite for 10 minutes. Dimensions of the disinfected impressions and their resultant casts were measured using a computerized digital caliper, and the dimensional changes were calculated. Reproduction of detail and surface quality of the resultant casts were assessed by grading casts surfaces according to a specific scoring system. RESULTS: The 0.5% sodium hypochlorite was found to produce the least dimensional changes in all the impression materials. Corsodyl produced the maximum changes in both alginate and zinc-oxide eugenol while addition-cured silicon was most affected by Gluteraldehyde and condensation-cured silicon was most affected by Hexana. The dimensional changes, however, were minimal and clinically insignificant. Addition-cured silicon showed the best surface quality and dimensional stability followed by condensation-cured silicon. Alginate and zinc-oxide eugenol had poorer surface quality and were affected to a higher extent by the disinfection procedures. CONCLUSIONS: The results were comparable with the standard specifications for dimensional stability. Recommendations were made for the use of 10 minutes immersion in 0.5% sodium hypochlorite as the most appropriate disinfection protocol to the investigated impression materials. KEYWORDS: Disinfectants; Gypsum casts; Impressions; Alginate; Addition-cured silicone; Sodium hypochlorite.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".