Bibliographic record
Abstract
Vascular and Interventional Radiology, more succinctly known as Interventional Radiology (IR), is the subspecialty of Medical Imaging or Radiology that deals with diagnosis and treatment using minimally invasive procedures under imaging guidance. Initially, fluoroscopy was the only imaging modality available, but ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) are also currently being used for guidance. One of the basic skills used by interventional radiologists is the Seldinger technique: the introduction of a needle into a body cavity or lumen allowing passage of a wire guide, which in turn facilitates the insertion of a tube or catheter. Many IR procedures have supplanted more invasive surgical techniques, with the resultant benefits of lower morbidity and mortality, shorter hospital stays and recovery times, and lower costs. Traditionally, obstetricians and interventional radiologists seldom interacted with one another, but their collaboration in patient care and research is increasing as obstetricians realise the value of IR, and as the myriad techniques and tools in the interventionalist's armamentarium expand and evolve.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".