THIS Standards document is intended as a Supplement to the Recommended Reporting Standards for Vena Cava Filter Placement and Patient Follow-
Bibliographic record
Abstract
there has been increased interest in non-permanent vena cava filters, with both increased research and clinical use of these devices. Several such de-vices are now approved for use in Eu-rope, Canada, and the United States. The previous Standards did address several issues related specifically to non-permanent filters: this document contains additional issues that have arisen in the interval. Although there is a large number of publications regarding vena cava fil-ters, the literature is generally limited, with few good prospective studies,
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 | 0.105 | 0.369 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.021 | 0.014 |
| Insufficient payload (model declined to judge) | 0.080 | 0.100 |
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".