Predictability of ClinCheck in Overbite Correction with Aligners: A Systematic Review
Bibliographic record
Abstract
Background: The use of aligner therapy for open bite and deep bite correction has increased in contemporary society. There is no evidence that unify the results present the in literature regarding a real comparison between clinical outcomes and the results predicted by the ClinCheck software 3.0 (Align Technology, Santa Clara, CA, USA). Furthermore, the literature shows conflicting data about the protocols and not all authors compare the programmed movements and the clinical results obtained for the overbite correction. Therefore, the aim of this systematic review is to assess the predictability of ClinCheck in the correction of vertical discrepancies by comparing the planned outcomes with the actual clinical results performed with clear aligners. Methods: The research question focused on the effectiveness of ClinCheck in predicting the actual correction of deep bite AND open bite in adult patients. Five electronic databases (PubMed, Scopus, Embase, Web of Science and Cochrane Library) were investigated, with the following keywords: overbite AND aligners. A quality assessment was performed using the Newcastle-Ottawa scale, while the risk of bias was evaluated using the ROBINS-I tool 2.0. PROSPERO ID: CRD420251078610. Results: Out of a total of 838 records initially screened, seven studies fulfilled the inclusion criteria and were ultimately selected for this systematic review. The analysis focused on assessing the divergence between the overbite correction predicted by ClinCheck and the outcomes observed in clinical practice. Conclusions: ClinCheck demonstrated a predictability of 62.1% for overbite correction in open bite cases and 41.5% in deep bite cases. However, not all studies report the planned tooth movements. Among the studies that addressed this aspect, the majority reported no significant association between the overbite correction predicted during treatment planning and the results ultimately achieved—except for one study, which demonstrated significant accuracy in achieving absolute extrusion in the correction of open bite.
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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 | 0.016 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".