Identification of human cytotoxic ILC3s
Bibliographic record
Abstract
Abstract Human ILCs are classically categorized into five subsets; cytotoxic CD127 − CD94 + NK cells and non‐cytotoxic CD127 + CD94 − , ILC1s, ILC2s, ILC3s, and LTi cells. Here, we identify a previously unrecognized subset within the CD127 + ILC population, characterized by the expression of the cytotoxic marker CD94. These CD94 + ILCs resemble conventional ILC3s in terms of phenotype, transcriptome, and cytokine production, but are highly cytotoxic. IL‐15 was unable to induce differentiation of CD94 + ILCs toward mature NK cells. Instead, CD94 + ILCs retained RORγt, CD127 and CD200R1 expression and produced IL‐22 in response to IL‐15. Culturing non‐cytotoxic ILC3s with IL‐12 induced upregulation of CD94 and cytotoxic activity, effects that were not observed with IL‐15 stimulation. Thus, human helper ILCs can acquire a cytotoxic program without differentiating into NK cells.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".