Autoanticuerpos y vasculitis sistémicas
Bibliographic record
Abstract
The term vasculitis includes a heterogeneous group of diseases that have in common inflammatory injury of the blood vessels. The evolution of this inflammatory process leads to ischemia or, sometimes, haemorrhage of the organs dependent on these vessels. The location of the affected vessels and tissues will determine the appearance of a wide variety of clinical manifestations and, therefore, a very variable prognosis.The different entities grouped under the term vasculitis include Wegener's granulomatosis, Churg-Strauss syndrome, classical panarteritis nodosa, microscopic polyangeitis, Kawasaki disease and classical leukocyte vasculitis, which predominantly affect small and medium-sized vessels. Giant cell arteritis and Takayasu arteritis mainly affect large vessels. We can find primary vasculitis (without association with another underlying disease) or secondary to both infectious processes and autoimmune diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.). Neutrophil anticitoplasma antibodies (ANCA) were initially described by Davies et al. (2) in patients with glomerulonephritis. They are directed against enzymes present in the granules.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".