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
Regulating gene expression is an effective way for cells to deal with various stresses. The outcome of this regulation differs with the type of stress, and can promote either cell survival or cell death depending on the severity of the injury incurred. Gene expression can be controlled at several steps, including transcription, translation and degradation. An extensively studied protein involved in translational control is the eukaryotic translation initiation factor 2 (eIF2). When eIF2 becomes phosphorylated on a specific serine residue located within the alpha (alpha) subunit, global protein synthesis is halted. This phosphorylation occurs following periods of environmental stress, and plays a significant role in the cellular response to these events. The eIF2alpha kinase family consists of four members, which are each activated in response to different stimuli. Our group has recently discovered that two members of this family, the protein kinase activated by double-stranded RNA (PKR) and the PKR-like endoplasmic reticulum (ER) kinase (PERK) can also regulate the expression of specific proteins by promoting their degradation by the 26S proteasome. Specifically, we demonstrated that degradation of the cell cycle regulator cyclin D1, and the tumour suppressor p53 was promoted by PERK and PKR during periods of ER stress. This novel function may allow the eIF2alpha kinases to affect a larger number of cellular processes than previously believed.
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 | 0.000 | 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) | 0.000 | 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