Occlusive retinal vasculitis and periphlebitis in Buerger’s disease: a case report
Bibliographic record
Abstract
Thromboangiitis obliterans (TAO), also known as Buerger’s disease, is a segmental occlusive nonatherosclerotic inflammatory condition of small and medium sized arteries and veins of the upper and lower extremities [ 1 ]. Leo Buerger originally described the condition in 1908 among young Polish and Russian Jews in New York city. Buerger’s originally proposed pathologic process involved the concept of a thromboarteritis or thrombophlebitis, rather than the proliferative or obliterating process derived from the intima of the arteries and veins (obliterating endarteritis.) Consensus today is that TAO is a different entity from closely related pathologic disorders, such as arteriosclerosis obliterans and thromboembolism and can involve other vascular territories including cerebral, coronary, renal and mesenteric arteries [ 2 ]. The etiology of this condition remains unknown, but tobacco is thought to play a critical role in its pathophysiology. For that reason, the diagnostic criteria for TAO includes positive smoking history, in addition to onset prior to 50 years of age, infra-popliteal arterial occlusive disease, upper limb involvement or phlebitis migrans, and the absence of atherosclerotic risk factors except smoking [ 3 ].
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".