Professional Insights from a Pioneer in Autoimmune Disease Testing: The Future of Antinuclear/Anticellular Antibody Testing
Bibliographic record
Abstract
Almost half a century has lapsed since I embarked on a career-long study of systemic autoimmune rheumatic diseases (SARDs)2 with a focus on their autoantibodies directed against an astounding spectrum of cellular antigens (1). The discovery of the lupus erythematosus cell and the development of the lupus erythematosus cell test serves as a historic reference point for the study of antinuclear antibodies (ANAs), or what today international consensus advocated should more correctly be referred to as anticellular antibodies (ACAs) (2, 3). Paralleling the explosion of the spectrum of ACAs was a remarkable transition in the technologies used to detect autoantibodies (1). Although some of the “octogenarian” assays such as double immunodiffusion, hemagglutination, complement fixation, and counterimmunoelectrophoresis are fading into oblivion, the ACA indirect immunofluorescence (IIF) test is increasingly used as a screening test and entry criterion for SARD. However, the emergence of newer multianalyte array technologies that have higher throughput, sensitivity, and specificity and detect a broader range of autoantibodies in comparatively miniscule serum samples may eventually replace the ACA …
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".