Evaluation of Contamination Reduction on Gypsum Casts from Alginate Impressions Disinfected with Four Different Materials
Bibliographic record
Abstract
INTRODUCTION: Infection control is one of the most important aspects in dentistry. According to the special features of dentistry, this profession can have a very important role in transmission of infection. This study was conducted by comparing the effects of four common disinfectants on the microbial contamination of alginate impressions and corresponding gypsum casts. METHODS & MATERIAL: In this experimental study, eleven patients aged 20-30 years old were selected by convenience sampling method. Six alginate impressions for each patient were formed by 24-hour intervals. These sixty six alginate impressions were divided in six groups (control-no wash, wash with water, Micro10, 2% Glutaraldehyde, 5.25% Sodium hypochlorite and Deconex). Disinfection methods were done by spraying (except for glutaraldehyde group that was done by immersing method) and then the alginate impressions were placed in plastic bags for 10 minutes to prevent the evaporation of disinfectants. Sixty six gypsum casts were made from alginate impressions. Microbial swabs were collected from mid palatal region of alginate impressions and gypsum casts for all groups by dried sterile cotton. The swabs were cultured for bacteria by inoculation on Blood Agar at 37°C for 3 days. The positive cultures were counted and the data was analyzed by software SPSS21. RESULTS: The counting colonies of gypsum casts and alginate impressions which were disinfected by Micro10, 2% Glutaraldehyde, 5.25% Sodium hypochlorite and Deconex were not statistically significant and meaningful. CONCLUSION: All disinfectants used in this study, had the same and acceptable effect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".