MétaCan
Menu
Back to cohort
Record W4415270125 · doi:10.1016/j.jobcr.2025.10.010

A custom-made appliance for mandibular mobilization in children with limited mouth opening

2025· article· en· W4415270125 on OpenAlexaff
Mahdis Maleki, Sally Elshennawy, Paniz Haghighi, Taras Masnyi, Κ. Ν. Stevens

Bibliographic record

VenueJournal of Oral Biology and Craniofacial Research · 2025
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMobilizationCurrent (fluid)Oral cavityMandible (arthropod mouthpart)Sample (material)

Abstract

fetched live from OpenAlex

Introduction: Limited mouth opening can impact oral function and hygiene, necessitating surgical intervention. Adjunctive appliance therapy has been shown to improve postoperative outcomes. At The Hospital for Sick Children (SickKids), a customized Mandibular Opening Appliance (MOA) was developed to enhance jaw mobility post-surgery. Methods: A retrospective chart review was conducted for seven patients who completed MOA therapy at our orthodontic clinic between 2021 and 2024, using data from patients' charts. Maximum incisal opening (MIO) was recorded pre-surgery, post-surgery, following MOA use, and follow-up. Results: Pre-surgical MIO ranged from 5 to 17 mm, with a mean of 8.8 ± 5.2 mm. Among the five patients with good to excellent compliance, final MIO ranged from 18 to 42 mm, representing a mean increase of 23.2 ± 9.2 mm (range: 13-36 mm). In contrast, two patients with poor compliance showed only minimal improvement (2 mm and 4 mm). Conclusions: These findings demonstrate the efficiency of the MOA in improving MIO in compliant pediatric patients. Incorporating such appliances post-surgery shows potential for improving mandibular mobility and supporting long-term outcomes. Although a larger sample size is needed to strengthen the evidence, current results remain compelling and support refining appliance protocols for this patient population.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.418
Teacher spread0.366 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oral Biology and Craniofacial ResearchSame topicOrthodontics and Dentofacial OrthopedicsFrench-language works237,207