Bibliographic record
Abstract
Understanding antibody repertoires and in particular, the properties and fates of B cells expressing potentially pathogenic antibodies is critical to define the mechanisms underlying multiple immunological diseases including autoimmune and allergic conditions as well as transplant rejection. Moreover, an integrated knowledge of the antibody repertoires expressed by B cells and plasma cells (PC) of different functional properties and longevity is essential to develop new therapeutic strategies, better biomarkers for disease segmentation, and new assays to measure restoration of B-cell tolerance or, at least, of normal B-cell homeostasis. Reaching these goals, however, will require a more precise phenotypic, functional and molecular definition of B-cell and PC populations, and a comprehensive analysis of the antigenic reactivity of the antibodies they express. While traditionally hampered by technical and ethical limitations in human experimentation, new technological advances currently enable investigators to address these questions in a comprehensive fashion. In this review, we shall discuss these concepts as they apply to the study of Systemic Lupus Erythematosus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".