Bibliographic record
Abstract
Background: Minimally invasive procedures have become increasingly popular because they require minimal downtime and are effective for achieving a more youthful appearance. All U.S. Food and Drug Administration-approved neurotoxins are indicated for achieving similar effects, even though they are different in regard to structure, manufacturing technique, and storage requirements. It is agreed upon that each neurotoxin is unique and therefore not interchangeable. The aim of the author is to provide an approach for choosing the optimal toxin in different indications regarding the area of treatment, the age and characteristics of the patient, potential risks, and ultimate goals. Methods: As the country that the author practices carries onabotulinum (ONA), prabotulinum (PRA), and abobotulinum (ABO) toxin type-A, one of these three toxins was preferred for each category. ABO toxins were preferred in wide areas due to the broader action halo. Typical examples include hyperhidrosis treatment, wide forehead area, and calf slimming. In areas where very precise and targeted treatment is required, PRA and ONA toxins were preferred to limit potential side effects due to wider diffusion. First-time patients were typically treated with PRA toxins for a softer trial periods where as "repeat" patients were successfully treated with ABO toxins. Results: No toxin is superior to the other in terms of producing effects. Yet, small differences in their properties can allow the plastic surgeon to cater to each patient's needs while yielding the most optimal results. Conclusions: This study is meant to serve as a guideline for choosing the ideal toxin in different patient settings and indications.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".