Autoimmune hepatitis: From current knowledge and clinical practice to future research agenda
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Autoimmune hepatitis is a chronic inflammatory liver disease. Unknown triggers lead to a mainly T cell-mediated immune response targeting the liver, the main auto-antigen of which has not been identified yet. The diagnosis of autoimmune hepatitis is based on the elevation of immunoglobulin G/hypergammaglobulinemia, detection of characteristic autoantibodies as well as a typical pattern on liver histology. Exclusion of other causes of hepatitis and response to immunosuppressive treatment support the diagnosis of autoimmune hepatitis. The mainstay of autoimmune hepatitis treatment has, from its first description to the current time, consisted of predniso(lo)ne to induce remission, in combination with azathioprine, which is used to maintain it. Nonetheless, side effects and non-response with ongoing inflammation despite standard therapy demand treatment alternatives. Only through a better understanding of the pathogenesis of autoimmune hepatitis can a more selective and effective treatment be offered to patients in the future. Until this goal is reached, improvement of diagnostic approaches and optimization of current therapy rank highest on the research agenda for autoimmune hepatitis.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it