Inborn errors of immunity (primary immunodeficiencies)
Bibliographic record
Abstract
Primary immunodeficiencies (PID), now often referred to as inborn errors of immunity (IEI), are a large heterogeneous group of disorders that result from deficiencies in immune system development and/or function. IEIs can be broadly classified as disorders of adaptive immunity (e.g., combined or humoral immunodeficiencies) or of innate immunity (e.g., phagocyte and complement disorders). Although the clinical manifestations of IEIs are highly variable, traditionally many disorders involve an increased susceptibility to infection. Research in recent years has underscored how IEI can present with features other than infection such as: severe atopy, autoimmunity, autoinflammation, lymphoproliferation, and/or malignancy resulting from immune dysregulation. Early consultation with a clinical immunologist is essential, as timely diagnosis and treatment are imperative for preventing significant disease-associated morbidity and mortality. The treatment of IEIs is complex and generally requires both supportive and definitive strategies, including but not limited to, immunoglobulin replacement therapy, antibiotic prophylaxis, immune response modifiers, and hematopoietic stem cell transplantation. This article provides an overview of the major categories of IEIs and strategies for the appropriate diagnosis and management of these disorders.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".