Bibliographic record
Abstract
Introduction Spurred by recent developments in molecular neurobiology, the 1990s have seen a burgeoning of interest in the genetic aspects of cerebrovascular diseases. Many types of cerebrovascular lesions are associated with well-defined, genetically determined conditions: cerebral aneurysms accompany polycystic kidney disease; cerebral arteriovenous malformations (AVM) are a major component of hereditary haemorrhagic telangiectasia (HHT, Rendu–Osler–Weber disease); and cerebral cavernous angiomas are associated with at least two genetic mutations (Lozano & Leblanc, 1992; Putnam et al., 1996; Gunel et al., 1995). In this context the elaboration of a new neurocutaneous syndrome, hereditary neurocutaneous angiomatosis (HNA), a condition characterized by the presence of vascular lesions of the skin and brain, is of interest because its molecular characterization may shed light on the etiology of common sporadic cerebrovascular lesions such as AVMs and developmental venous anomalies (DVA) with which it is associated (Zaremba et al., 1979; Hurst & Baraitser, 1988; Leblanc et al., 1996). Most AVMs and DVA are sporadic lesions without associated cutaneous anomalies. Clinical manifestations Cutaneous manifestations The clinical manifestations of the vascular nevi in HNA depend on their size and location. The lesions, including cavernous angiomas, AVMs, and venous malformations, are multiple and they can range from a few millimetres in apparent diameter to up to 1–2 cm. The color of the lesions depends on their depth, the deeper ones appearing as a flat bluish discoloration, the more superficial and larger ones as elevated, bluish or reddish, raspberry-like, blanching, compressible structures (Fig. 21.1). Palpable phleboliths are sometimes present.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".