Developing Consensus in the Assessment and Treatment Pathways for Autoimmune Encephalitis in Child and Adolescent Psychiatry
Bibliographic record
Abstract
Children with a diagnosis of Autoimmune Encephalitis (AE) frequently require multi-disciplinary care in order to mobilize the assessment and treatment necessary for recovery. Institutional and provider practice differences often influence the diagnostic workup and treatment pathways made available to patients. There are a variety of provider coalitions in pediatric rheumatology, internal medicine, and neurology that have been making meaningful progress toward the development of consensus in assessment and treatment approaches to patient care. However, child psychiatry is currently underrepresented in this work in spite of the high psychiatric symptom burden seen in some young patients. The need for consensus is often made visible only with inter-institutional dialogue regarding patient care trajectories. We aim to review key updates in the assessment and treatment of children and adolescents with autoimmune encephalitis during the acute phase, with or without catatonia, and to outline provider perspectives by comparing current treatment models in the United States, Canada, and Europe.
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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 | 0.070 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".