The Effect of Earlier Bone Grafting, Prior to Orthodontic Treatment, on SWAG Ratings of Graft Outcomes
Bibliographic record
Abstract
Objective: To compare the outcomes between 2 groups of patients with complete clefts treated with early secondary alveolar bone grafting (ABG) at 2 centers (5-7 years, before orthodontic intervention) and to a third group of patients treated at one of those centers (center 1) who had received later secondary ABG (8-10 years, after orthodontic intervention). Design: Blind retrospective analysis of cleft site radiographs using Americleft Standardized Way to Assess Grafts (SWAG) scale. Patients: A total of 99 patients with complete clefts from 2 North American cleft/craniofacial centers. Interventions: Secondary ABG representing 2 protocols: early grafting at a mean age of 6.6 years prior to any orthodontic intervention, and later grafting at a mean age of 10.2 years following pregrafting orthodontic intervention. Main Outcome Measures: Using occlusal radiographs, the SWAG scale from 0 (failed graft) to 6 (ideal) was used. Six trained, calibrated raters scored each radiograph twice, with the average of the 2 ratings used as the final score. Reliability was assessed using the weighted κ statistic. The significance of differences between groups was determined using the Kruskal-Wallis test and Dunn test for pairwise comparisons. Results: Inter-rater reliability of SWAG method was good (0.631). Intra-rater reliability was excellent (0.817). There was a tendency for improved total graft outcome in the early grafted group from center 1 compared to the later grafted group with improvement being significantly different in only the coronal third of the early, preorthodontic grafted group. However, the difference was not statistically significant for the graft overall.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".