Comparison of Morphological Measurements Extracted From Digitized Dental Radiographs With Lumbar and Femoral Bone Mineral Density Measurements in Postmenopausal Women
Bibliographic record
Abstract
BACKGROUND: We set out to determine whether morphologic measurements extracted from digitized images of bite-wing radiographs correlated with lumbar and femoral bone mineral density (BMD) measurements in 45 postmenopausal women who had no or only mild periodontal disease (no probing depths >5 mm). METHODS: Lumbar spine and femoral BMDs were determined by dual-energy x-ray absorptiometry. Vertical bite-wing radiographs were taken and digitized. Crestal and apical regions of interest (ROIs) were drawn on the digital images of the maxillary and mandibular alveolar bone on the patient's right and left sides. For each patient, a single morphologic measurement was made for each of 8 ROIs. Correlation analysis was performed to determine the strengths of the relationships between the morphologic measurements made at the 8 locations and between these morphologic measurements and BMD measurements. RESULTS: The correlations (r) between the morphologic operator (MO) measurements and lumbar spine and femoral BMDs were weak (mean r = 0.02, range = 0.32 to -0.26) and not statistically significant, with no clear trends discernible. Correlations between MO measurements made at the 8 alveolar sites were also weak (mean r = 0.05, range = 0.35 to -0.38) and not statistically significant. CONCLUSIONS: The MO measurements used in this study were weakly correlated with lumbar spine and femoral BMDs, with no clear trends discernible in this population of postmenopausal women with no or mild periodontal disease.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".