Bibliographic record
Abstract
This chapter focuses on the epidemiology, pathophysiology, clinical manifestations, diagnosis, prognosis, and treatment of two entities of the Thrombotic microangiopathy (TMA) spectrum: Shiga toxin-producing Escherichia coli-associated hemolytic uremic syndrome (STEC-HUS) and complement-mediated TMA. STEC-HUS is more frequent in children than in adults, with median age around two years, although adults have more severe disease with higher mortality. The common pathologic basis of all TMA is injury to the vascular endothelium with subsequent microvascular thrombosis, which leads to consumptive thrombocytopenia, microangiopathichemolytic anemia, and kidney and other organs injury. The clinical symptoms of TMA reflect anemia, thrombocytopenia, and renal or other organ involvement, and include pallor, fatigue, shortness of breath, oliguria, and edema. HUS is an entity under the umbrella of TMA. The most common cause, STEC-HUS, has long been considered as independent of the rest of this spectrum of diseases as it has a defined trigger and known secondary cause of microangiopathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".