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Record W3205894973 · doi:10.3390/jcm10204730

Three-Dimensional Evaluation of Condyle-Glenoid Fossa Complex Following Treatment with Herbst Appliance

2021· article· en· W3205894973 on OpenAlexaff
Jasmine Nindra, Maninder Singh Sidhu, Anuraj Singh Kochhar, Ashish Dabas, Rosa Valletta, Roberto Rongo, Gianrico Spagnuolo

Bibliographic record

VenueJournal of Clinical Medicine · 2021
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCondyleFossaMalocclusionDentistryMaxillaOrthodonticsSurgery

Abstract

fetched live from OpenAlex

The purpose of the present retrospective observational study was to compare the effects of treatment with Herbst appliance and fixed therapy with elastics on the condyle and glenoid fossa complex. Thirty patients aged between twelve and sixteen years with skeletal Class II malocclusion who met the inclusion criteria were included in the study: fifteen patients treated with Herbst appliance (Group 1), and fifteen patients treated with orthodontic camouflage using MBT prescription (MBTTM Versatile+ Appliance System) (Group 2). For Group 2, patients had CBCT scans taken before treatment either after Herbst appliance removal or at the end of treatment. CBCT scans were evaluated for changes in condyle-glenoid fossa complex using the In Vivo Dental 5.1 software. Statistical significance was set at p ≤ 0.05. On inter-group comparison, the Herbst group showed statistically significant increases in the condylar height of 1.35 mm (p ≤ 0.001) on the right and 1.21 mm (p ≤ 0.01) on the left side, and a condylar volume of 111.03 mm3 (p ≤ 0.01) on the right and 127.80 mm3 (p ≤ 0.001) on the left side. The Herbst group showed anterior remodelling on the postero-superior aspect of glenoid fossa. Herbst appliance treatment induced growth at the condylar head and anterior remodelling of glenoid fossa, thereby improving the maxilla-mandibular relationship in growing skeletal Class II patients.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.125
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.245
GPT teacher head0.472
Teacher spread0.227 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

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