Bibliographic record
Abstract
1. Anne K. Junker, MD* 1. *Associate Professor, Division of Infectious and Immunological Diseases, Department of Pediatrics, University of British Columbia and Children’s & Women’s Health Centre of British Columbia, Vancouver, BC, Canada Author Disclosure Dr. Junker did not disclose any financial relationships relevant to this article. After completing this article, readers should be able to: 1. Outline the epidemiology of primary Epstein-Barr virus (EBV) infection. 2. Describe and explain the physiologic basis of the clinical features of infectious mononucleosis. 3. Describe and explain the physiologic basis of the common complications of infectious mononucleosis. 4. List the diagnostic tests that can help distinguish acute primary from distant past EBV infection. 5. Review the EBV-associated lymphoproliferative disorders and malignancies. EBV was identified initially in 1964 in tumor tissue from a patient who had African Burkitt lymphoma (BL), a rapidly growing, usually fatal malignancy of the B lymphocyte. When a laboratory technician working with this new virus became ill with mononucleosis and seroconverted to EBV, the link between EBV and mononucleosis became apparent. Soon thereafter, seroepidemiologic studies revealed that EBV infects virtually all of the world’s population, usually as a subclinical or trivial illness in childhood. A decade later, reports of a familial X-linked disorder of fatal infectious mononucleosis highlighted the importance of immunogenetic factors in the management of EBV infection. Now, nearly 40 years after its discovery, EBV continues to captivate clinicians, virologists, oncologists, geneticists, and immunologists attempting to understand this highly successful human pathogen. EBV is a ubiquitous, worldwide pathogen that is harbored persistently by virtually all adults, regardless of geographic location. After primary infection, the virus latently infects circulating B cells and is shed silently into saliva and genital secretions. The colloquial term “kissing disease” acknowledges the oral route by which most people are infected. Spread is associated with close personal contact, so it is not surprising that the age at first infection varies according to living conditions. Infection occurs at an earlier age in the presence of poor hygiene and crowded living conditions; infection rates in …
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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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.038 |
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".