Bibliographic record
Abstract
In this issue of Neurology ®, Deiva et al.1 describe the CNS features of primary hemophagocytic lymphohistiocytosis (HLH), a rare genetic immunodeficiency disorder associated with macrophage activation. Microcephaly, seizures, encephalopathy, abnormal spinal fluid (elevated protein, cellularity, or more specifically, hemophagocytosis), and periventricular white matter lesions characterize the CNS features of HLH, with progressive cognitive decline occurring in surviving, nontransplanted children. Of 46 children with HLH, 63% had abnormal neurologic examination, 50% had abnormal spinal fluid, and 33% had abnormal brain MRI. Encephalopathy, multifocal neurologic deficits, and young age at onset renders challenging the distinction of HLH from acute disseminated encephalomyelitis (ADEM). Deiva et al. specifically compared the MRI features of the 46 children with HLH to those of 44 children with ADEM. Although both HLH and ADEM are characterized by bilateral, multifocal areas of increased T2 signal, the lesion distribution of HLH preferentially involved the periventricular white matter, and rarely involved the deep gray nuclei or brainstem. Although none of the MRI features were absolutely discriminatory, the relative involvement and symmetric nature …
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".