Evaluation of the plaque removal efficacy of a water flosser compared to string floss in adults after a single use.
Bibliographic record
Abstract
OBJECTIVE: To compare the plaque removal efficacy of a water flosser to string floss combined with a manual toothbrush after a single use. METHODS: Seventy adult subjects participated in this randomized, single-use, single-blind, parallel clinical study. Subjects were assigned to one of two groups; Waterpik Water Flosser plus a manual toothbrush (WF) or waxed string floss plus a manual toothbrush (SF). Each participant brushed for two minutes using the Bass technique. The WF group added 500 ml of warm water to the reservoir and followed the manufacturer's instructions, and the SF group used waxed string floss between each tooth, cleaning the mesial and distal surfaces as instructed. Subjects were observed to ensure they covered all areas and followed instructions. Scores were recorded for whole mouth, marginal, approximal, facial, and lingual regions for each subject using the Rustogi Modification of the Navy Plaque Index. RESULTS: The WF group had a 74.4% reduction in whole mouth plaque and 81.6% for approximal plaque compared to 57.7% and 63.4% for the SF group, respectively (p < 0.001). The differences between the groups showed the water flosser was 29% more effective than string floss for overall plaque removal and approximal surfaces specifically (p < 0.001). The WF group was more effective in removing plaque from the marginal, lingual, and facial regions; 33%, 39%, and 24%, respectively (p < 0.001). CONCLUSION: The Waterpik Water Flosser and manual toothbrush is significantly more effective than a manual brush and string floss in removing plaque from tooth surfaces.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".