A Comparison of Commercially Available Polymethylmethacrylate-Based Soft Tissue Fillers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND The rapid market expansion of filler treatment options requires physicians and health care providers to fully understand differences among comparable products. OBJECTIVE The objective was to compare commercially available polymethylmethacrylate (PMMA)-based soft tissue fillers to determine if there are meaningful variations in these products that could result in significantly different therapeutic profiles, especially with respect to safety. METHODS AND MATERIALS PMMA particles were evaluated for size and morphology using scanning electron microscopy (SEM) techniques. PMMA microsphere soft tissue filler products from the United States, Europe, Brazil, and Canada were compared with respect to size, homogeneity/irregularity, surface smoothness/roughness, and the presence or absence of sediment and particulate debris. RESULTS Marked differences with respect to PMMA particle morphology and related particle characteristics from a variety of products were found. Of note, some products demonstrated potentially concerning significant variability in particle size and irregular morphology. CONCLUSION It is anticipated that the variability detected in these products, based on the literature, could result in different therapeutic profiles, especially with respect to safety. Physicians and health care providers should be aware that "comparable" products that at a glance appear similar may not be equal.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 it