Bibliographic record
Abstract
The high-affinity binding interactions between interferons (IFNs) and their cognate cell surface receptors lead to the activation of receptor-associated Janus protein tyrosine kinases (Jaks) and subsequent phosphorylation and activation of a group of transcription factors, the signal transducers and activators of transcription (Stats). Upon IFN-induced activation, these Stat proteins form homodimeric and heterodimeric complexes that translocate to the nucleus and bind specific elements within the promoters of IFN-stimulated genes (ISGs). In addition to the well-studied IFN-induced ISG factor 3 (ISGF3) and Stat1:1 complexes, IFNs induce the formation of a number of other Stat-containing complexes, including Stat3:3 and Stat5:5 homodimers, as well as Stat2:1 and Stat5:CrkL heterodimers, that also mediate gene transcription. Moreover, emerging evidence suggests that particular amino acid residues within the individual Stat proteins contribute to different aspects of Stat function. These residues modulate the transcriptional activation potential of Stat-containing complexes and thereby influence the expression of ISGs. Indeed, the Stat proteins function in a multifaceted manner to regulate the expression of proteins that mediate IFN responses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".