Bibliographic record
Abstract
Primary immunodeficiencies (PID) can present with recurrent infections, autoimmunity, inflammation, or malignancy and each of these conditions can be associated with elevated immunoglobulin. A high level of immunoglobulin G (IgG) is an uncommon finding, especially in pediatrics, and does not rule out primary immunodeficiency. Deficiencies in varied aspects of immune response have been described with high IgG. Reported PID conditions with elevated IgG include defects in humoral, cellular, and innate immunity. Some of these immunodeficiencies can have fatal outcomes, some require hematopoetic stem cell transplantation, and some require systemic medications. The mechanisms driving elevated IgG are not well understood, but in some cases abnormal cytokine production has been proposed. The evaluation of a patient with high IgG is guided by the patient's history and a physical examination, with special attention to autoimmunity in pediatrics and malignancy and liver disease in adults. In the setting of autoimmunity, chronic gastrointestinal disease, or chronic infections, the measurement of specific antibodies to evaluate the function of the IgG should be considered. An increased appreciation of elevation in IgG reflecting immune dysregulation may lead to earlier PID diagnoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".