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
Insulin rapidly activates protein synthesis by activating components of the translational machinery including eIFs (eukaryotic initiation factors) and eEFs (eukaryotic elongation factors). In the long term, insulin also increases the cellular content of ribosomes to augment the capacity for protein synthesis. The rapid activation of protein synthesis by insulin is mediated primarily through phosphoinositide 3-kinase. This involves the activation of PKB (protein kinase B). In one case, PKB acts to phosphorylate and inactivate glycogen synthase kinase 3, which in turn phosphorylates and inhibits eIF2B. Insulin elicits the dephosphorylation and activation of eIF2B. Since eIF2B is required for recycling of eIF2, a factor required for all cytoplasmic translation initiation events, this will contribute to overall activation of protein synthesis. PKB also phosphorylates the TSC1 (tuberous sclerosis complex 1)-TSC2 complex to relieve its inhibitory action on the mTOR (mammalian target of rapamycin). Inhibition of mTOR by rapamycin markedly impairs insulin-activated protein synthesis. mTOR controls translation initiation and elongation. The cap-binding factor eIF4E can be sequestered in inactive complexes by 4E-BP1 (eIF4E-binding protein 1). Insulin elicits phosphorylation of 4E-BP1 and its release from eIF4E, allowing eIF4E to form initiation factor complexes. Insulin induces dephosphorylation and activation of eEF2 to accelerate elongation. Both effects are blocked by rapamycin. Insulin inactivates eEF2 kinase by increasing its phosphorylation at several mTOR-regulated sites. Insulin also stimulates synthesis of ribosomal proteins by promoting recruitment of their mRNAs into polyribosomes. This is inhibited by rapamycin. Several key questions remain about, for example, the mechanisms by which mTOR controls 4E-BP1 and eEF2 kinase and the control of ribosomal protein translation.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 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