Review: elastic compression stockings prevent post-thrombotic syndrome in patients with deep venous thrombosis
Bibliographic record
Abstract
Kolbach DN, Sandbrink MW, Hamulyak K, et al . Non-pharmaceutical measures for prevention of post-thrombotic syndrome. Cochrane Database Syst Rev 2004;(1):CD004174 (latest version 21 Aug 2003). Q Are non-pharmaceutical interventions effective and safe for preventing post-thrombotic syndrome (PTS) in patients with deep venous thrombosis (DVT)? ### ![Graphic][1]</img>Data sources: Cochrane Peripheral Vascular Diseases Specialised Trials Register (January 2003), which is based on searches of Medline and EMBASE/Excerpta Medica; Cochrane Central Register of Controlled Trials (2002); hand searches of Scripta Phlebologica (1993–2000), J Thromb Haemost (2003), conference proceedings, and citations of identified studies; and experts in the field. ### ![Graphic][2]</img>Study selection and assessment: randomised controlled trials (RCTs) or clinical controlled trials that compared medical elastic stockings (pressure 20–30 mm Hg or 30–40 mm Hg … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".