Consensus statement on surgical pathology of the aorta from the Society for Cardiovascular Pathology and the Association for European Cardiovascular Pathology: I. Inflammatory diseases
Bibliographic record
Abstract
Inflammatory diseases of the aorta include routine atherosclerosis, aortitis, periaortitis, and atherosclerosis with excessive inflammatory responses, such as inflammatory atherosclerotic aneurysms. The nomenclature and histologic features of these disorders are reviewed and discussed. In addition, diagnostic criteria are provided to distinguish between these disorders in surgical pathology specimens. An initial classification scheme is provided for aortitis and periaortitis based on the pattern of the inflammatory infiltrate: granulomatous/giant cell pattern, lymphoplasmacytic pattern, mixed inflammatory pattern, and the suppurative pattern. These inflammatory patterns are discussed in relation to specific systemic diseases including giant cell arteritis, Takayasu arteritis, granulomatosis with polyangiitis (Wegener's), rheumatoid arthritis, sarcoidosis, ankylosing spondylitis, Cogan syndrome, Behçet's disease, relapsing polychondritis, syphilitic aortitis, and bacterial and fungal infections.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".