Autoimmune Hepatitis: Clinical Manifestations and Diagnostic Criteria
Bibliographic record
Abstract
In 1998, the International Autoimmune Hepatitis Group--a panel of 40 hepatologists and hepatopathologists from 17 countries who have a particular interest in autoimmune hepatitis (AIH)--undertook a review, in light of subsequent experience, of the descriptive criteria and diagnostic scoring system that it had proposed in 1993 for the diagnosis of AIH. This review (published in 1999) noted that the original descriptive criteria appeared to be quite robust and required only relatively minor modifications to bring them up to date with developments and experience in diagnostic modalities for liver disease in general. Analysis of published data on the application of the original criteria in nearly 1000 patients revealed that the diagnostic scoring system had an overall diagnostic accuracy of 89.8%, with a sensitivity of 98.0%. Specificity for excluding definite AIH in patients with chronic viral hepatitis and circulating autoantibodies or patients with overlapping cholestatic syndromes was 98% to 100%, but specificity for excluding probable AIH in these disorders ranged from only 60% to 80%. Modifications, including adjustments to the weightings against biochemical and histological cholestatic features, have been made to the scoring system to improve its specificity.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".