Stats: Multifaceted Regulators of Transcription
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
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 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 | 0.003 |
| 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 it