Extracellular‐regulated kinase—mitogen‐activated protein kinase cascade: Unsolved issues
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
This review point out several aspects regarding the mitogen-activated protein kinase (MAPK)/extracellular-regulated kinase (Erk) network, which are still pending issues in the understanding how this pathway integrate information to drive cell fates. Focusing on the role of Erk during cell cycle, it has to be underlined that Erk downstream effectors, which are required for mitosis progression and contribute to aneuploidy during tumorigenesis, remain to be determined. In addition to the identity of the terminal enzymes or effectors of Erk, it has to be stressed that the dynamic nature of the Erk signal is itself a key factor in cell phenotype decisions. Development of biophotonics strategies for monitoring the Erk network at the spatiotemporal level in living cells, as well as computational and hypothesis-driven approaches, are called to unravel the principles by which signaling networks create biochemical and biological specificities. Finally, Erk dynamics might also be impacted by other post-translational modification than phosphorylation, such as O-GlcNAcylation.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| 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