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Record W2586295640 · doi:10.4317/jced.53434

Effect of orthodontic treatment involving first premolar extractions on mandibular third molar angulation and retromolar space

2017· article· en· W2586295640 on OpenAlexaff
Luz Mendoza-García, Esther Vaillard Jiménez, A Garcia-Rocha, Carlos Bellot‐Arcís, Vanessa Paredes‐Gallardo

Bibliographic record

VenueJournal of Clinical and Experimental Dentistry · 2017
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsMolarPremolarMedicineOrthodonticsDentistryMandibular first molarMandibular second molarMandibular third molar

Abstract

fetched live from OpenAlex

BACKGROUND: Third molars present more problems than other teeth because they are the last teeth to erupt, and so it is important to assess their development when designing an orthodontic treatment plan. The aim of this study was to compare the angulation of the mandibular third molar and retromolar space before and after orthodontic treatment in cases involving first premolar extraction. MATERIAL AND METHODS: 76 patients, 59 women (77.63%) and 17 men (22.36%), were recruited from the Orthodontics Clinic at Benemérita Universidad Autónoma de Puebla (Mexico). Panoramic radiographs were analyzed before and after orthodontic treatment that included first premolar extractions, measuring retromolar space (RS) and the angles formed by the intersection of the axes of the third and second molar (α) and the intersection of the axis of the mandibular plane and third molar (β). RESULTS: The data obtained underwent statistical analysis. The angle α and β showed statistically significant differences on the left side in women. In men, only the right side α angle showed significant differences. Retromolar space increased significantly on both sides for both sexes. CONCLUSIONS: Third molar, retromolar space, orthodontics.

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 score0.040
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.053
GPT teacher head0.418
Teacher spread0.364 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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