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SKELETAL AND DENTAL CHANGES INDUCED BY BIONATOR IN EARLY TREATMENT OF CLASS II

2016· article· en· W2536572119 on OpenAlexaff
Dirceu Barnabé Raveli, João Paulo Schwartz, Taísa Boamorte Raveli, Ary dos Santos-Pinto, Bryan Tompson

Bibliographic record

VenueActa Scientiarum Health Sciences · 2016
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMalocclusionDentistryOrthodonticsCephalometry

Abstract

fetched live from OpenAlex

The purpose was to investigate the amount of skeletal and dentoalveolar changes after early treatment of Class II, Division 1 malocclusion with bionator appliance in prepubertal growing patients. Forty Class II patients were divided in two groups. Treated group consisted of 20 subjects treated consecutively with bionator. Mean age at the start of treatment (T0) was 9.1 years, while it was 10.6 years at the end of treatment (T1). Mean treatment time was 17.7 months. Pretreatment and post-treatment cephalometric records of treated group were evaluated and compared with a control group consisted of 20 patients with untreated Class II malocclusion. Intergroup comparisons were performed using Student’s t-tests and chi-square test with Yates’ correction at a significance level of 5 per cent. Bionator appliance was effective in generating differential growth between the jaws. Cephalometric skeletal measurements ANB, WITS, Lafh, Co-A and dental L6-Mp, U1.Pp, IsIi, OB, OJ showed statistically significantly different from the control. Bionator induced more dentoalveolar changes than skeletal during treatment in prepubertal stage.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.037
GPT teacher head0.330
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2016
Admission routes1
Has abstractyes

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