Understanding immune mechanisms to create novel treatments for primary biliary cholangitis
Bibliographic record
Abstract
Understanding immune mechanisms to create novel treatments for primary biliary cholangitis Professor Channakeshava S Umeshappa from Dalhousie University discusses the burden of primary biliary cholangitis and how understanding immune mechanisms may help to treat it. Primary biliary cholangitis (PBC) is characterised by chronic inflammation of the interlobular bile ducts, leading to fibrosis, cirrhosis, and liver failure if left untreated. Symptoms of PBC include fatigue, jaundice, itchy skin, abdominal pain, nausea or vomiting, dry eyes and mouth, and bone and joint aches. The incidence of PBC is increasing worldwide,(1) but is most common in Europe and North America.(2) PBC has a female predominance, affecting primarily middle-aged women (over 90% of the PBC cases). Clinically, it is often diagnosed by detecting anti-mitochondrial autoantibodies and elevated alkaline phosphatase enzymes in blood tests.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".