Bibliographic record
Abstract
This meeting brought together some of the world's leading scientists in the field of stress signaling, apoptosis, and cancer. This resulted in a productive interaction that updated our current knowledge on "Stress Signaling in Cancer." It comes out that subtle disturbances in cell signaling can be associated with and even lead to cancer. As a corollary, it appears that correcting the signaling defects associated with cancer constitutes a new approach to the treatment and control of neoplastic diseases. The meeting also raised several questions that should be addressed. In particular, it is of the utmost importance to better understand the mechanisms that underlie the specificity of the cellular response with regard to different ligands. For example, why does Gadd45b prevent apoptotic cell death in response to tumor necrosis factor alpha, whereas it favors apoptosis after transforming growth factor beta (E. De Smaele et al.). Other questions concern the understanding of the cross-talk mechanisms between different stress and apoptotic pathways and how the strength and the position and timing of a signal may affect different pathways. The next few years of research in this field should be enlightening and fruitful.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".