Bibliographic record
Abstract
The B and T lymphocytes of the specific immune response use complex gene rearrangement machinery to generate a wide diversity of antigen receptors capable of recognizing any pathogen in the universe. Binding to receptors on both innate and specific immune system cells triggers intricate intracellular signaling pathways that lead to new gene transcription and effector cell activation. And yet, regulation is imposed on these responses so that paradise is not lost to the turning of the immune system onto self-tissues, the spectre of autoimmunity. Lymphocyte activation requires multiple signals and intercellular interactions. Mechanisms exist to establish tolerance to self by the selection and elimination of cells recognizing self-antigens. Immune system cell populations are reduced by programmed cell death and/or necrosis once the pathogen threat is resolved. Once good health is reestablished, memory cells remain in the body to sharply reduce the impact of a second exposure to a pathogen. Over the last two decades, our laboratory had been engaged in studying the molecular signaling pathways that confer cell survival or cell death in these lymphocytes. The special role of fas in germinal centre B cells survival, the function of the CARMA1/Bcl-10/Malt1 complex in the differentiation and survival of the various subsets of lymphocytes, the intriguing task of IL-7 in maintaining T cell effector functions, and the importance of nfil3 the development of NK cells will be presented.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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; both teacher heads agree on what is shown here.
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".