The plaque removal efficacy of a novel power brush head.
Bibliographic record
Abstract
OBJECTIVE: To assess the plaque removal efficacy of an oscillating/rotating power toothbrush with novel brush head (Oral-B Precision Clean) in comparison to an American Dental Association (ADA) reference manual toothbrush. METHODS: This was a replicate-use, single-brushing, two-treatment, examiner-blind, randomized, four-period (visit) study with a crossover design. At each visit, subjects disclosed their plaque with disclosing solution for one minute, and an examiner performed a baseline (pre-brushing) plaque examination (Rustogi, et al. Modification of the Navy Plaque Index). Subjects were then instructed to brush for two minutes (according to manufacturer's instructions) with their assigned power toothbrush or as they normally do with the ADA manual brush under supervision, after which they again disclosed their plaque and were given a post-brushing plaque examination. RESULTS: Both the power brush and manual brush showed statistically significant plaque reductions from baseline for the whole mouth, along the gingival margin, and on approximal surfaces. The power brush showed statistically significant advantages (p < 0.001) over the manual brush in plaque reduction for whole mouth (28.8%), gingival margin (44.3%), and approximal surfaces (20.7%). CONCLUSION: The oscillating/rotating power toothbrush with a novel brush head showed statistically significantly superior plaque reduction (whole mouth, gingival margin, and approximal surfaces) compared to a manual toothbrush.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".