Bibliographic record
Abstract
Costimulatory and coinhibitory mechanisms appear to be involved throughout immune responses to control their specificity and level. Many mechanisms operate; therefore, various theoretical models should be considered complementary rather than competing. One such coinhibitory model, pictured in 1971, involves the crosslinking of antigen receptors with inhibitory Fc receptors by antigen/antibody complexes. This model was prompted by observations that the Fc portion of antibody was required for potent suppression of immune responses by antibody. The signal via the antigen receptor wakes up T or B cells, providing specificity, while costimulators and coinhibitors stimulate or inhibit these awoken cells. The recent observations that administration of monoclonal anti-SARS-CoV-2 spike antibodies in early COVID-19 patients inhibits the induction of clinically damaging autoimmune antibodies suggest they may provide negative Fc signals that are blocked in COVID-19 patients. Furthermore, the reduced ability of SARS-CoV-2 antigen to localize to germinal centres in COVID-19 patients also suggests a block in binding of the Fc of antibody bound to antigen on FcγRIIb of follicular dendritic cells. The distinction between self and foreign is made not only at the beginning of immune responses but also throughout, and involves multiple mechanisms and models. There are past beginnings (history of models) and current and future beginnings for solving serious clinical problems (such as COVID-19) and different types of models used for understanding the complexities of fundamental immunology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".