Bibliographic record
Abstract
Presently, the orthotropic liver transplantation (OLT) is still the most effective therapeutic for patients with acute or chronic hepatic failure. However, due to the shortage of donor livers, the number of patients benefited from this approach is limited. Therefore, some alternative modalities have been paid attention for restoring the liver function. The cell transplantation is one of the promising modalities to realize this purpose. The types of cells used in the cell transplantation include syngeneic hepatocytes, allogeneic hepatocytes, immortalized hepatocytes, and stem cells derived heptocytes. The stem cells, especially the adult stem cells from bone marrow, are shown as a promising cell source for liver repopulation. The mesenchymal bone marrow stem cells and embryonic stem cells can be induced to differentiate into the hepatic lineage and might be used in the cell transplantation for liver diseases. Compared to OLT, the advantages of cell-based therapy for liver disease are, but not limited to, less invasive, less expensive, easy manipulated, easy expansion of cells in vitro. Cells can be stored in a cell bank for future use. Though most of the current studies are experimental and animal based, the cellular therapy for liver disease is expected to be an effective alternative in clinical settings in near future.
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.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
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".