Creating Tight Proximal Contacts for MOD Resin Composite Restorations
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare proximal contact tightness (PCT) of MOD resin composite restorations placed with different matricing protocols. METHODS: Forty-five ivorine lower right first molars with standardized MOD cavities were equally divided into three groups according to the restoration protocol. Group 1: Sectional matrix (Standard matrix, Palodent, Dentsply) secured with a wedge (Premier Dental Products Co.) and separation ring (BiTine I, Palodent, Dentsply, York, PA, USA) was used to restore the mesial surface first and then removed and repeated for the distal surface. Group 2: Identical to group 1, but separation rings were placed at both the mesial and distal sides (BiTine I+II, Palodent) prior to restoration. Mesial surface was restored followed by distal. Group 3: Walser matrix (O-form, Dr. Walser Dental GmbH) was used. Following composite resin restoration, PCT was measured using the tooth pressure meter. Data were analyzed using analysis of variance and a Tukey post hoc test (p<0.05). RESULTS: PCT values for mesial contacts were 2.99 ± 0.47N for group 1, 4.57 ± 0.36N for group 2, and 3.03 ± 0.79N for group 3. For the distal contacts, the values were 4.46 ± 0.44N for group 1, 5.12 ± 0.13N for group 2, and 0.76 ± 0.77N for group 3. Significantly tighter contacts were obtained for mesial and distal contacts for group 2 compared to groups 1 and 3 (p<0.05). For groups 1 and 3, mesial contacts were not significantly different (p=0.993), while distal contacts for group 1 were significantly tighter (p<0.001). CONCLUSION: Within the limitations of this study, tighter contacts can be obtained when sectional matrices and separation rings are applied to both proximal surfaces prior to placement of the resin composite in MOD cavities.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".