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Record W2976199236 · doi:10.4317/jced.56169

Dentoalveolar changes in adults promoted by the use of auxiliary expansion arch: A cbct study

2019· article· en· W2976199236 on OpenAlexaff
Gustavo Silva Siécola, JFC Henriques, Guilherme Janson

Bibliographic record

VenueJournal of Clinical and Experimental Dentistry · 2019
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsDental archArchMedicineCone beam computed tomographyOrthodonticsDentistryMolarComputed tomographySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The objective of this study was to evaluate the dentoalveolar effects and the changes of buccal cortical bone in the posterior area after expansion obtained with TMA auxiliary expansion arch in adult patients. MATERIAL AND METHODS: A retrospective analysis of CT scans of 13 patients (6 male, 7 female) treated at a private clinic, taken immediately before and after the use of an auxiliary expansion archwire, was performed. Mean age at installation of TMA auxiliary expansion arch was 29.23 years (s.d.=9.13) and the mean age when the auxiliary arch was removed was 29.52 years (s.d.=9.16). Mean time of the use of the TMA auxiliary expansion arch was 0.29 years (s.d.=0.09). The patients used fixed appliances and after leveling and alignment, a TMA auxiliary expansion arch was installed, combined with the primary 0.017x0.025-inch thermoactivated Ni-Ti archwire. CBCT scans were taken at T1 and T2. Linear and angular measurements regarding the positioning of maxillary molar, premolars and canines were performed. Intragroup comparison of the variables at T1 and T2 was performed with dependent t tests. RESULTS: There was statistically significant transverse increase and buccal inclination of all teeth. The cortical bone showed adaptability and displacement in the same direction of tooth movement, but in smaller amounts. CONCLUSIONS: Cone-Beam Computed Tomography, Maxillary Expansion, Adult treatment.

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 score0.011
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.106
GPT teacher head0.399
Teacher spread0.293 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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