Bibliographic record
Abstract
Innate lymphoid cells (ILCs) are increasingly being recognized for their ability to impact both innate and adaptive immune cells in diverse contexts. ILCs have been observed in all secondary lymphoid tissues, in addition to being tissue-resident innate lymphocytes. In these locations, ILCs are poised to interact with various immune cells at different stages of an immune response. While the heterogeneity and plasticity of ILCs has complicated their study, their association with immune dysregulation in a wide range of pathologies highlights their importance to human health and disease. Notably, in addition to promoting inflammatory immune responses, populations of ILCs have been shown to inhibit immune responses through a variety of mechanisms. The reports of ILC-mediated regulation of immune responses have differed in terms of the phenotype of the regulatory ILC populations, and their mechanism of action. Yet the ability to modulate immune responses appears to be an important function of ILCs. As our understanding of this family of lymphocytes evolves, delineating the factors that dictate whether ILCs orchestrate inflammatory immune responses or suppresses these responses will be important for understanding various disease mechanisms. Here we focus on recent reports that examine how ILCs regulate immunity in different contexts.
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 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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".