Bibliographic record
Abstract
The recently concluded Tenth International Congress on Systemic Lupus Erythematosus (SLE) held in Buenos Aires was a resounding success. This overview summarizes some of the origins of the First International Congress held in Calgary, Canada in 1986, predictions offered by past Congress Presidents, and a perspective on the trends in autoantibody testing, which remains one of the key approaches to the early and accurate diagnosis of SLE. The last few decades have witnessed a remarkable proliferation of new diagnostic technologies including addressable laser bead immunoassays and, more recently, chemiluminescence and lateral flow technologies that could find a clinical niche in point-of-care diagnostics. Against the backdrop of these constantly emerging technologies, indirect immunofluorescence has remained the platform of choice for many laboratories and diagnosticians. The notion that autoantibodies are pathogenic has been challenged by evidence that some autoantibodies are protective, some may have catalytic capacity while others may be neutral or have no function at all. The latter notion of functionless or "junk" autoantibodies needs to be taken under some advisement, because there was a time when a great proportion of the human genome was considered to include "junk DNA". The butterfly as a symbol of hope and progress in SLE research over the past 27 years since the First International Congress on SLE is almost certainly to be even more appropriate when future Congresses are held in Geneva (2015), Melbourne (2017) and eventually one in 2050.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".