Plaque removal efficacy of a novel tooth wipe.
Bibliographic record
Abstract
OBJECTIVE: This study was designed to evaluate the safety and plaque removal efficacy of a tooth wipe (Oral-B Brush-Ups) using a manual toothbrush as a control. METHODOLOGY: Twenty-five healthy subjects from a general population were enrolled in this randomized, single-use, crossover study. After 23-25 hours of no oral hygiene, oral hard and soft tissues were examined, and disclosed plaque was scored using the Turesky, et al. modification of the Quigley Hein Plaque Index. Subjects used their randomly assigned product for a timed period of one minute without instruction, after which hard and soft tissues and plaque scores were reassessed. Subjects returned to the clinic after a one-week washout period, and the clinical procedures were repeated before and after use of the alternate product. All clinical measurements were made by one examiner who was masked to treatment sequence. RESULTS: Both the tooth wipe and toothbrush were found to be safe, and significantly reduced plaque levels from whole mouth, facial, and lingual surfaces (p < 0.0001). The toothbrush removed significantly greater plaque than the tooth wipe (p < 0.0001) on whole mouth surfaces (49% vs. 29%), facial surfaces (71% vs. 44%), and lingual surfaces (25% vs. 13%). CONCLUSION: The tooth wipe provides an effective method of plaque removal when tooth brushing is not practical.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".