Bibliographic record
Abstract
Interferon (IFN)-gamma is a cytokine produced mostly by activated T cells and NK cells that has complex effects on immune and nonimmune cells. IFN-gamma plays important roles in inflammation, usually in synergy with other cytokines, such as IL-1beta and TNF-alpha. The uniqueness of IFN-gamma lies in its ability to induce major histocompatibility complex (MHC) expression in many tissues, making it particularly relevant to transplantation. The results of graft rejection in the absence of IFN-gamma show that IFN-gamma modulates but is not essential for the allogeneic responses, suppressing generation of CTL. In vivo IFN-gamma has a protective role early in the response to vascularized organ allografts: transplants in mice have a tendency to develop necrosis when IFN-gamma is not available, apparently by failure of the microcirculation. The lack of IFN-gamma greatly reduces the induction of MHC in organ allografts, and it is possible that this is indirectly related to the protective effect of IFN-gamma. Nevertheless IFN-gamma also promotes graft vessel disease later in the course ofthe transplant. Thus IFN-gamma has diverse and potentially contradictory effects on organ allograft survival, acting both on the immune system and on the graft itself, the net effect depending on the graft type and the time post-transplant.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".