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Record W2054719568 · doi:10.2319/123013-950.1

Anterior maxillary dentoalveolar and skeletal cephalometric factors involved in upper incisor crown exposure in subjects with Class II and III skeletal open bite

2014· article· en· W2054719568 on OpenAlexaff
Luis Ernesto Arriola‐Guillén, Carlos Flores‐Mir

Bibliographic record

VenueThe Angle Orthodontist · 2014
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOverbiteIncisorMedicineDentistrySagittal planeOrthodonticsCephalometryOcclusionOverjetMalocclusionCephalometric analysisSurgeryAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the anterior dentoalveolar and skeletal maxillary cephalometric factors involved in excessive upper incisor crown exposure (UICE) in subjects with skeletal open bite Class II (SOBCIIG) and Class III (SOBCIIIG) against an untreated control group (CG). MATERIALS AND METHODS: Seventy pretreatment lateral cephalograms of orthodontic young adult patients (34 men, 36 women) were examined. The sample was divided into three groups according to both sagittal and vertical growth pattern and occlusion. The CG group (n = 25) included Class I, normodivergent cases with adequate overbite, and the SOBCIIG group (n = 25) and SOBCIIIG group (n = 20) included skeletal Class II or III malocclusions, respectively, with hyperdivergent pattern and negative overbite. Several cephalometric measurements were considered (skeletal and dental). Analysis of variance, multivariate analysis of covariance, and Tukey HSD post hoc tests were used. Principal component analysis (PCA) was used for reducing the number of cephalometric variables related to UICE. Finally, a multiple linear regression was calculated. RESULTS: Significant differences in UICE were found between the groups (P < .05). UICE was 3.9 mm in SOBCIIG, 2.5 mm in SOBCIIIG, and 0.4 mm in CG. PCA showed that a nondental component-including vertical maxillary height (VMH) and upper lip height (ULH)-was the only component significantly associated with UICE. The regression model had a moderate prediction capability. CONCLUSIONS: Although the UICE was statistically different in SOBCIIG, the values were within the esthetic standards. The UICE was mainly influenced by VMH and ULH.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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.

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

Citations10
Published2014
Admission routes1
Has abstractyes

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