�젙留κ린�삎�뿉 ���븳 寃쏀솕�슂踰뺤쓽 移섎즺�슚怨�
Bibliographic record
Abstract
Background: Although surgical excision is the standard method for the treatment of venous malformations, this procedure often leads to massive bleeding and cosmetic problems. Sclerotherapy for venous malformations has recently been reported, whereas sclerotherapy for varicose veins, leg telangiectasias and hemorrhoids has well been established. \n\nObjective: To assess the usefulness of sclerotherapy for venous malformations. \n\nMethod: Fourteen patients who had venous malformation were treated with sclerotherapy using sodium tetradecyl sulfate (Thromboject�뱡, Omega Laboratories, Ltd., Montreal, Canada). Clinical efficacy was evaluated by physical examination and comparison of photographs. \n\nResults: In patients with venous malformations, 71.4% of the eases showed moderate to marked improvement. Side effects were noted in 6 patients, however, they were trivial and transient and no treatment was needed. \n\nConclusion: Sclerotherapy can be recommended as an effective method for the treatment of venous malformations. It has milder and fewer side effects than other treatment modalities, and it also yields superior cosmetic results.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.016 | 0.004 |
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".