Influence of abrasive particle size on surface properties of flowable composites
Bibliographic record
Abstract
The purpose of this investigation was to measure and compare both the surface roughness and gloss of flowable composites polished with standardized silicone carbide (SiC) papers. Four flowable and two conventional composites were used in this study. Polymerized specimens were subjected to a polishing procedure comprising 12 sequential steps from coarser to finer grits of SiC paper. At the initial polishing stage, flowable composites were more sensitive to the size of the polishing particles and thus yielded surfaces rougher than the conventional composites. Surface roughness became stable when polishing particles less than 13 microm size were used. However, although surface roughness was reduced, an esthetic gloss quality was not achieved on the resultant polished surface. On the influence of filler shape, composites with spherical fillers seemed to have the upper-hand advantage of attaining a high gloss by polishing. On the influence of polishing particle size, it was suggested that polishing should be completed with polishing particles less than 12 microm size so as to achieve clinically satisfactory surface roughness and gloss.
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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) | 0.000 | 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".