Efficacy of the GentleWave System in the removal of biofilm from the mesial roots of mandibular molars before and after minimal instrumentation: An ex vivo study
Bibliographic record
Abstract
AIM: To compare the efficacy of Enterococcus faecalis biofilm removal using the GentleWave System (GWS) (Sonendo Inc, CA) on non-instrumented versus minimally instrumented root canal systems. METHODOLOGY: Thirty-four mandibular molars were autoclaved and allocated to four groups: Negative control (n = 5); positive control (n = 5); Group 1: non-instrumentation + GWS (NI + GWS) (n = 12); and Group 2: minimal instrumentation + GWS (MI + GWS) (n = 12). Of 34 samples, 24 samples with Vertucci type 2 configuration within the mesial root of each sample were allocated to Groups 1 and 2 and then matched based on the working length and root canal configuration. After inoculation of samples with E. faecalis for 3 weeks, the GWS was used on Group 1 without any instrumentation and Group 2 after instrumentation of mesial canals until size 20/06v. CFU and SEM analysis were used. RESULTS: (CFU/mL) from the positive control, and Group 1 and 2 were 7.41 ± 0.53, 3.41 ± 1.54, and 3.21 ± 1.54, respectively. Both groups showed a statistically significant difference in the reduction of viable E. faecalis cells compared to the positive control (Group 1 [p = .0001] and Group 2 [p < .0001]), whilst showing no significant difference between the two tested groups (p < .05). CONCLUSION: The use of GWS on the non-instrumented root canal system could be an effective disinfection protocol in removing the biofilm without dentin debris formation.
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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 | 0.000 |
| 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".