Effect of Surface Characteristics on Adherence of S. mutans Biofilms to Indirect Resin Composites
Bibliographic record
Abstract
The purpose of this study was to evaluate the adherence of biofilms to the surfaces of two indirect resin composites, Estenia C&B and Gradia. Slabs were prepared from the materials, and then either ground with 800-grit silicon carbide paper or polished with diamond pastes up to 1 microm. Artificial biofilms of Streptococcus mutans were grown on the composite slabs in an artificial mouth system for 20 hours. Thereafter, the amounts of retained biofilm on the surfaces were measured after sonication. Surface characteristics of the resins--such as surface roughness, amount of residual monomers, and distribution of filler particles--were examined. Two-way ANOVA revealed that the amount of retained biofilm varied (p<0.05) according to the composition and surface roughness of the material. In particular, biofilm adherence was lowest on Estenia C&B slabs when polished with diamond pastes up to 1 microm. It was thus concluded that the surface roughness and composition of a resin composite influenced biofilm adherence.
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 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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".