Reliability of the SWAG—The Standardized Way to Assess Grafts Method for Alveolar Bone Grafting in Patients with Cleft Lip and Palate
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to test a new method, a Standardized Way to Assess Grafts (SWAG), to rate alveolar bone graft (ABG) outcomes for patients with cleft lip and palate. DESIGN: This was a retrospective comparison using the SWAG scale. SETTING: This study took place in four cleft palate centers with different treatment protocols. METHODS: A total of 160 maxillary occlusal radiographs taken 3 to 18 months post-ABG for sequentially treated patients with cleft lip and palate were assessed using the SWAG scale. Radiographs were scanned, standardized, blinded, and rated by 6 calibrated orthodontists to assess vertical thirds, bony root coverage, and complete bony fill. All radiographs were rated twice, 24 hours apart, by the same raters. MAIN OUTCOMES: Intra- and interrater reliabilities were assessed. RESULTS: Intrarater reliability was good to very good (.760; .652-.834), and interrater reliability was moderate to good (.606; .569-.681), comparable to previously published methods. CONCLUSIONS: Rater reliabilities were shown to be comparable to or better than existing methods. The SWAG method was validated for ABG assessments in the mixed and permanent dentitions based on reliabilities in an intercenter outcome comparison.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Intra- and inter-rater reliability of a radiographic scale for grading bone grafts; clinical instrument reliability in the measurement sense, a polysemy trap rather than metaresearch.
This study tests the reliability of a clinical graft-assessment instrument rather than research practice.
Interrater reliability of a clinical graft-assessment scale; clinical measurement validation, polysemy trap not research reproducibility.
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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".