Idiopathic condylar resorption in adolescents: A scoping review
Bibliographic record
Abstract
OBJECTIVE: Idiopathic condylar resorption (ICR), also known as progressive condylar resorption, is poorly understood, particularly in adolescent patients. Therefore, this scoping review aims to summarize the available literature on the prevalence, aetiology, pathogenesis, diagnostic process, treatment and/or any outcome regarding ICR in adolescent individuals. METHODS: This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and its extension for scoping reviews (PRISMA-ScR), as well as Joanna Briggs Institute studies. The search strategy was defined adopting a core search structure for each source, and the search was performed on MEDLINE, EMBASE, Cochrane Library, Web of Science, Scopus and Google Scholar. After duplicate removal, two independent reviewers screened abstracts, followed by complete articles, to achieve the definition of included studies. Data collection was performed, and the extracted data were organized in tabular form, along with a narrative summary of main findings that aligns with the objective of this review. RESULTS: Six observational studies were included in this review. Three studies focused on signs and symptoms, one on prevalence and signs and symptoms, one on treatment and one on disease pathogenesis. CONCLUSION: This scoping review revealed inadequate published research regarding prevalence, aetiology, early diagnosis, pathogenesis and treatment of ICR in adolescents.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".