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Record W2089513019 · doi:10.1597/13-272

Presurgical Cleft Lip Anthropometrics and Dental Arch Relationships in Patients with Complete Unilateral Cleft Lip and Palate

2014· article· en· W2089513019 on OpenAlexaff
Gregory S. Antonarakis, Alex Adibfar, Bryan Tompson, John Daskalogiannakis, David M. Fisher

Bibliographic record

VenueThe Cleft Palate-Craniofacial Journal · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineAnthropometryDentistryArchDental archOrthodontics

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate associations between anthropometric lip measurements and dental arch relationships in patients with complete unilateral cleft lip and palate (CUCLP). DESIGN: Retrospective cross-sectional study. PATIENTS: Children with CUCLP. METHODS: Anthropometric lip measurements, made immediately prior to lip repair, were available for each patient. The dental arch relationships were evaluated on dental study casts (8.6 ± 0.9 years) taken prior to any orthodontic treatment and prior to alveolar bone graft, using the modified Huddart and Bodenham (MHB) scoring system. The presence of associations between anthropometric lip measurements and dental arch relationships was determined using linear regression analysis. RESULTS: In the 63 patients included in the study, the cleft lateral lip element was deficient in height in 87% and in transverse width in 86% of patients. Patients with more deficient cleft-side lateral lip height were more likely to present with more negative MHB scores (r = .443; P < .001). Conversely, patients with more deficient cleft-side lateral lip transverse width more often presented with more positive MHB scores (r = .281; P = .025). CONCLUSIONS: In patients with CUCLP, there is a wide variability in the degree of deficiency of the cleft-side lateral lip element, both in the vertical and in the transverse dimension. The extent of this deficiency may, in part, predict the resulting dental arch relationships.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

Explore more

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