External root resorption (ERR) and rapid maxillary expansion (RME) at post-retention stage: a comparison between tooth-borne and bone-borne RME
Bibliographic record
Abstract
Abstract Background The study aimed to compare external root resorption (ERR) three-dimensionally in subjects treated with tooth-borne (TB) versus bone-borne (BB) rapid maxillary expansion (RME). Forty subjects who received tooth-borne RME (TB group, average age 13.3 years ± 1.10 years) or bone-borne RME (BB group, average age 14.7 ± 1.15 years) were assessed using CBCT imaging before treatment (T0) and after a 6-month retention period (T1). 3D reconstructions of the radicular anatomy of maxillary first molars (M1), first and second premolars (P1 and P2) were generated to calculate volumetric (mean and percentage values) and shape changes (deviation analysis of the radicular models) obtained at each time point. 2D assessment of radicular length changes was also performed for each tooth. Data were statistically analyzed to perform intra-group (different teeth) and inter-group comparisons. Results In both groups, all the investigated teeth showed a significant reduction in radicular volume and length (p < 0.05), with the first molars being the teeth most affected by the resorption process (volume and palatal root length). When volumetric radicular changes were calculated as a percentage of the pre-treatment volumes, no differences were found among the investigated teeth (p > 0.05). Based on the deviation analysis from radicular models superimposition, the areas most affected by shape change were the apex and bucco-medial root surface. Overall, the amount of ERR was significantly greater in the TB group (mm3: M1 = 17.03, P1 = 6.42, P2 = 5.26) compared to the BB group (mm3: M1 = 3.11, P1 = 1.04, P2 = 1.24). Conclusions Despite the statistical significance, the difference in the amount of ERR of the posterior maxillary dentition between TB-RME and BB-RME remains clinically questionable.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".