Biliary Atresia Animal Models: Is the Needle in a Haystack?
Bibliographic record
Abstract
Biliary atresia (BA) is a progressive fibro-obliterative process with a variable degree of inflammation involving the hepatobiliary system. Its consequences are incalculable for the patients, the affected families, relatives, and the healthcare system. Scientific communities have identified a rate of about 1 case per 10,000-20,000 live births, but the percentage may be higher, considering the late diagnoses. The etiology is heterogeneous. BA, which is considered in half of the causes leading to orthotopic liver transplantation, occurs in primates and non-primates. To consolidate any model, (1) more transport and cell membrane studies are needed to identify the exact mechanism of noxa-related hepatotoxicity; (2) an online platform may be key to share data from pilot projects and new techniques; and (3) the introduction of differentially expressed genes may be useful in investigating the liver metabolism to target the most intricate bilio-toxic effects of pharmaceutical drugs and toxins. As a challenge, such methodologies are still limited to very few centers, making the identification of highly functional animal models like finding a "needle in a haystack". This review compiles models from the haystack and hopes that a combinatorial search will eventually be the root for a successful pathway.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".