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Record W3084026652 · doi:10.1186/s13005-020-00235-1

Evaluation of the changes of orbital cavity volume and shape after tooth-borne and bone-borne rapid maxillary expansion (RME)

2020· article· en· W3084026652 on OpenAlexaff
Antonino Lo Giudice, Lorenzo Rustico, Vincenzo Ronsivalle, Carmelo Nicotra, Manuel O. Lagravère, Cristina Grippaudo

Bibliographic record

VenueHead & Face Medicine · 2020
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCone beam computed tomographyDentistryComputed tomographyNuclear medicineOrthodonticsSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess and compare volumetric and shape changes of the orbital cavity in patients treated with tooth-borne (TB) and bone-borne (BB) rapid maxillary expansion (RME). STUDY DESIGN: Forty adolescents with bilateral maxillary cross-bite received tooth-borne (TB group = 20; mean age 14.27 ± 1.36 years) or bone-borne (BB group = 20; mean age of 14.62 ± 1.45 years) maxillary expander. Cone-beam computed tomography (CBCT) were taken before treatment (T1) and 6-month after the expander activation (T2). Volumetric and shape changes of orbital cavities were detected by referring to a specific 3D digital technology involving deviation analysis of T1/T2 CBCT-derived models of pulp chamber. Student's t tests were used to 1) compare T1 and T2 volumes of orbital cavities in TB and BB groups, 2) compare volumetric changes and the percentage of matching of 3D orbital models (T1-T2) between the two groups. RESULTS: ) (p < 0.0001). This increment were significant between the two groups (p < 0.05) while no differences were found in the percentage of matching of T1/T2 orbital 3D models (p > 0.05). The areas of greater changes were detected in the proximity of the frontozygomatic and frontomaxillary sutures. CONCLUSION: TB-RME and BB-RME would not seem to considerably affect the anatomy or the volume of the orbital cavity in adolescents.

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)0.001
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 score0.245
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.309
Teacher spread0.258 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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