Dr Eng M. Tan: a tribute to an enduring legacy in autoimmunity
Bibliographic record
Abstract
At the age of ninety years, Dr Eng Meng Tan has had a remarkable impact on the accumulated knowledge of autoimmune diseases, including seminal findings in systemic lupus erythematosus (SLE) and a wide range of other autoimmune diseases. Dating to the first description of the Sm (Smith) autoantibody in SLE, his focus has been the use of autoantibodies as probes to identify and elucidate novel cellular molecules and then translating these discoveries into biomarkers and immunoassays for a wide range of these diseases and, later, cancer. He led efforts to standardize autoantibody nomenclature and testing protocols. Through his mentorship a great number of trainees and collaborators have had remarkably successful careers, and by that virtue he has garnered a remarkable continuing legacy.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".