Making patterns better design tools: Requirements analysis for a family of navigators for design pattern catalogs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Activated T lymphocytes modulate the level of many molecules on their cell surface, including cytokine receptors. This regulation of cytokine receptor expression affects the ability of T cells to respond to cytokines and thus influences the outcome of an immune response. The receptor for IFN-gamma, a proinflammatory cytokine, consists of two copies of a ligand binding chain (IFN-gammaR1) as well as two copies of a second chain (IFN-gammaR2) required for signal transduction. The expression of IFN-gammaR2 is down-regulated at the mRNA level on CD4+ T cells when they differentiate into the Th1, but not the Th2, phenotype. This down-regulation has been demonstrated to depend on the ligand, IFN-gamma, which is produced by Th1 but not Th2 T cells. The regulation of the cell-surface expression of IFN-gamma receptors during primary T cell activation has not been reported. Naive and differentiated T lymphocytes express IFN-gammaR1 at the mRNA level and as a cell-surface protein. In this study, we present evidence that cell-surface expression of IFN-gammaR1 is transiently down-regulated on the surface of naive CD4+ T cells shortly after TCR engagement. Furthermore, this down-regulation is not mediated by the ligand, IFN-gamma, but results from TCR engagement and can be inhibited by cyclosporin A.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it