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Record W4414523320 · doi:10.2319/032825-251.1

Clear aligners for Class II correction in growing patients: elastics vs mandibular advancement

2025· article· en· W4414523320 on OpenAlexaff
Heeyeon Suh, James Chen, Sandra Khong Tai, Heesoo Oh

Bibliographic record

VenueThe Angle Orthodontist · 2025
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsClass (philosophy)MalocclusionFocus (optics)Component (thermodynamics)

Abstract

fetched live from OpenAlex

Objectives: To evaluate the skeletal and dental effects of Class II correction in growing patients using clear aligners, with either elastics or mandibular advancement (MA). Materials and Methods: The study included 66 growing Class II patients: 45 patients treated with clear aligners (20 using Class II elastics and 25 with MA) and 21 untreated controls observed over a comparable time period. Nine cephalometric and three study cast measurements were evaluated initially (T1) and the end of treatment (T2) to assess skeletal and dental changes. Results: The control group maintained a Class II molar relationship and overjet, whereas both treatment groups corrected to Class I. In the MA group, statistically significant skeletal changes from T1 to T2 were observed, including reduction in SNA (-1.09°) and ANB (-1.69°), in addition to dentoalveolar Class II correction. The elastic group showed no statistically significant changes in SNA and ANB compared to the control group. Linear regression revealed 5.28° of lower incisor proclination with Class II elastics, whereas lower incisor inclination was maintained with MA treatment. Conclusions: Clear aligner treatment with Class II elastics and MA were effective for correcting Class II malocclusion in growing patients that would have otherwise been maintained without intervention. Although Class II correction was mainly due to dentoalveolar changes, a skeletal component was observed with MA treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.279
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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