A systematic review of cephalometric facial soft tissue changes with the Activator and Bionator appliances in Class II division 1 subjects
Bibliographic record
Abstract
The objective of the present systematic review was to evaluate, through lateral cephalograms, facial soft tissue changes after the use of the Activator and Bionator appliances in Class II division 1 malocclusion subjects. Several electronic databases (PubMed, Medline, Medline In-Process and Other Non-Indexed Citations, Cochrane Database, Embase, Web of Sciences, and Lilacs) were searched with the assistance of a senior health sciences librarian. Abstracts, which appeared to fulfil the initial criteria, were selected by consensus. The original articles were then retrieved. Their references were also hand searched for possible missing articles. Clinical trials, which assessed facial soft tissue changes with the use of either an Activator or a Bionator appliance without any surgical intervention or syndromic characteristics, were considered. A comparable untreated control group was required to factor out normal growth changes. Five articles using the Activator and six using the Bionator fulfilled the selection criteria and quantified facial soft tissue changes. An individual analysis of these articles was undertaken and some methodological flaws were identified. Based on the available evidence, a significant amount of controversy regarding the soft tissue changes produced by the Activator and the Bionator exists. Soft tissue changes that were reported as being statistically significant were of questionable clinical significance. Long-term, double-blinded, prospective randomized clinical trials are needed to confirm the findings. Three-dimensional quantification is also required to overcome current limitations in our understanding of the soft tissue changes obtained with the use of removable functional appliances.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".