Digital analysis of staining properties of clear aesthetic brackets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To analyse the staining properties of clear orthodontic brackets using a digital analysis. DESIGN: In vitro, laboratory study MATERIAL AND METHODS: A total of 500 tooth-coloured brackets from 10 brands (five ceramic and five plastic) were investigated. The cumulative discolouring effect of staining agents (tea, coffee, curry and red wine) were analysed at two consumption levels: light and heavy, based on a 6-month period of exposure. Study group brackets were immersed in the agents consecutively at 37°C. The control group was only exposed to artificial saliva. Samples were analysed digitally to obtain L*, a* and b* (lightness, red-green and yellow-blue) colour readings. Using these values, total colour change (ΔE*) at each level was also calculated. Three-way analysis of variance (ANOVA) test was used for statistical comparisons. RESULTS: L* and b* colour parameters showed significant differences (P<0·001) between different bracket groups, consumption levels and the type of exposure. However, the a* value only differed between bracket groups (P<0·001). According to the ΔE* values, ceramic brackets had less colour change than plastic brackets at the end of phase 1 for both the study and control groups. However, as consumption time increased, the rate of colour change decreased for the plastic brackets. In general, ceramic brackets demonstrated much more resistance to staining agents than plastic brackets. CONCLUSIONS: Both plastic and ceramic brackets showed changes in colour when exposed to heavy consumption of staining agents, with plastic brackets being the most affected.
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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 | 0.000 | 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) | 0.000 | 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 it