Influence of Passive Ultrasonic Irrigation on the Removal of Root Canal Filling Material in Straight Root Canals
Bibliographic record
Abstract
OBJECTIVE: This study evaluates the efficacy of passive ultrasonic irrigation (PUI) in removing root canal filling material from endodontically treated teeth after using one of two reciprocating systems, Reciproc (VDW, Munich, Germany) or WaveOne (Dentsply Maillefer, Ballaigues, Switzerland), or one nickel-titanium (NiTi) rotary system, ProTaper Universal Retreatment (Dentsply Maillefer). METHODS: One hundred and twenty straight root canals of extracted human maxillary incisors were instrumented and then obturated. The specimens were divided into six groups (n=20) as follows: Group R, Reciproc R25 instrument without PUI; Group W, WaveOne Primary instrument without PUI; Group PT, ProTaper Universal Retreatment system without PUI; Group R-PUI, Reciproc R25 with PUI; Group W-PUI, WaveOne Primary with PUI and Group PT-PUI, ProTaper Universal Retreatment system with PUI. After removing the filling material, the teeth were cleaved longitudinally and photographed. The total canal space and remaining material were quantified with the aid of an imaging software tool. The Kruskal-Wallis test was used to identify significant differences between the groups. RESULTS: No statistically significant differences (P>0.05) in residual filling material were observed between the groups. CONCLUSION: The use of PUI did not improve the removal of filling material from the root canals, regardless of the previously used instrumentation system.
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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".