Evaluation of efficacy of digital or virtual bite registration over conventional techniques- A systematic review
Bibliographic record
Abstract
Background: Bite registration procedures have been transformed by the digital revolution in dentistry, thus it is now necessary to compare the accuracy of digital or virtual techniques to conventional ones. Aim: To assess the accuracy of digital or virtual bite registration systems in comparison to conventional methods to clarify any potential advantages or disadvantages. Methodology: A thorough search in numerous databases, including PubMed, Embase, the Cochrane Library, Scopus, and Web of Science, was carried out in accordance with PRISMA criteria. The review focused on the accuracy of digital or virtual bite registration and covered a variety of study formats, including randomized controlled trials, clinical studies, and in-vitro investigations. For each of the included 7 studies, a thorough assessment of bias was conducted using the Newcastle-Ottawa Scale and the Cochrane Risk of Bias tool. As there would be expected variability in study designs, data synthesis required both a narrative explanation of the results and a qualitative synthesis. Results: This systematic review compared 7 studies on traditional bite registration methods versus digital/virtual techniques. Digital techniques highlighted improved efficiency and innovation with increased speed, accuracy, and integration advantages. Evaluations performed with the Newcastle-Ottawa Scale and ROBINS-I tool showed little bias in cross-sectional studies. Nevertheless, in vitro studies have identified biases in participant selection and result reporting, indicating a need for better study rigor and reporting standards. A study received a noteworthy 8 out of 9 score on the Newcastle-Ottawa Scale, indicating strong methodology with careful sample selection, solid comparability, and comprehensive outcome evaluation, enhancing its credibility in assessing bite registration techniques. Conclusion: The benefits of digital/virtual bite registration methods over traditional ones are demonstrated in this systematic review, which also shows how these methods improve speed, accuracy, and integration. Although some studies have shown biases, overall results support the validity and efficiency of digital techniques in improving dental practice.
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 | 0.001 |
| 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".