Evaluation of condylar changes in relation to various malocclusions: A systematic review
Bibliographic record
Abstract
Introduction: Variability in the size and shape of mandibular condyles among individuals of different sexes and ages may appear as a remodeling process to accommodate malocclusion. Hence, the aim of this study was to assess whether or not associations exist between different types of malocclusions and morphological modifications of the mandibular condyle. Materials and Methods: A systematic literature search was conducted on the Medline database via PubMed interface and supplemented by a manual search via Google Scholar to identify more articles reporting the subject of the review. A combination of controlled vocabulary was used in the search strategy and the final update was stopped on January 2021. The risk of bias was assessed based on the Newcastle–Ottawa Scale. Results and Discussion: Considering the preestablished inclusion and exclusion criteria, 20 articles were retained with 2607 human subjects (967 males/1299 females and 341 not specified, age: 4–60 years). Eighty percent of the selected articles reported associations between malocclusion and morphological changes of the condylar head. Sagittal plane malocclusions produce more changes to the temporomandibular joint components (head of condyle and joint space) (71.93%), while vertical malocclusions lead to the most severe manifestations. Conclusions: Cone-beam computed tomography is the most useful tool for the assessment of osseous morphology of mandibular head condyles and detection of cortical erosion (21.7%). Associations between morphological changes of the condylar head and specific types of malocclusions were proven. However, there is still a need for more clinical studies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".