Influence of the Amount of Toothpaste on Cleaning Efficacy: An In Vitro Study
Bibliographic record
Abstract
OBJECTIVES: study was to test the influence of the amount of toothpaste on enamel cleaning efficacy. MATERIALS AND METHODS: The hydrated silica-based test toothpaste (radioactive dentin abrasion: 60.19 ± 1.35) contained all ingredients of a regular fluoride toothpaste. The cleaning efficacy of four different toothpaste amounts (1.00 g, 0.50 g [both "full length of brush"], 0.25 g ["pea-size"], and 0.125 g ["grain of rice-size"]) diluted in 1.00 mL water were each tested for different brushing times (10, 30, 60, 120, 180, and 300 seconds) using a standardized staining model on human molars with a brushing machine. Photographic documentation and colorimetric measurements were conducted, respectively, initially, after staining and after each brushing step. Colorimetric measurements were used to calculate the stain removal (in %). STATISTICAL ANALYSIS: was set at ≤ 0.05. RESULTS: The cleaning efficacy decreased significantly when using smaller toothpaste amounts. Stain removal after 120 seconds brushing time was: 77.4 ± 5.0% (1.00 g toothpaste), 75.7 ± 3.4% (0.50 g toothpaste), 54.1 ± 6.7% (0.25 g toothpaste), and 48.2 ± 7.1% (0.125 g toothpaste), respectively. CONCLUSION: study the cleaning efficacy of a medium-abrasive, hydrated silica-based toothpaste was analyzed. Note that 1.00 g toothpaste showed for all brushing times a significantly higher cleaning efficacy than 0.25 g toothpaste and 0.125 g toothpaste.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".