Mechanisms of Alcoholic Liver Disease: Cytokines
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
This article represents the proceedings of a workshop at the 2000 ISBRA Meeting in Yokohama, Japan. The chair was Manuela G. Neuman. The presentations were (1) New aspects of hepatic fibrosis, by D. A. Brenner; (2) Cellular immune response in hepatitis C models, by B. Rehermann; (3) The role of interleukin-10 in acute alcoholic hepatitis, by J. Taieb, S. Chollet-Martin, M. Cohard, J. J. Garaud, and T. Poynard; (4) Cytokine-mediated apoptosis in vitro, by M. G. Neuman; (5) Signaling for apoptosis and repair in vitro, by G. G. Katz, R. G. Cameron, N. H. Shear, and M. G. Neuman; (6) Interferons activate the P42/44 mitogen-activated protein kinase and Janus Kinase signal transducers and activation of transcription (JAK-STAT) signaling pathways in hepatocytes: Differential regulation by acute ethanol via a protein kinase C-dependent mechanism, by B. Gao; (7) Genetic polymorphisms of interleukin-1 in association with the development of Japanese alcoholic liver disease, by M. Takamatsu, M. Yamauchi, M. Ohata, S. Saito, S. Maeyama, T. Uchikoshi, and G. Toda; and (8) Increased levels of macrophage migration inhibitory factor in sera from patients with alcoholic liver diseases, by T. Kumagi, S. M. F. Akbar, M. Abe, K. Michitaka, N. Horiike, and M. Onji.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it