Bibliographic record
Abstract
The regulatory mechanisms of cell survival and apoptosis are very complex in nature, implicating numerous players and signaling pathways not only in the decision-making process of surviving (or dying), but as well as in the execution of apoptosis itself. The same complex nature applies with regards to anoikis, a form of apoptosis that is largely regulated by integrin-mediated, cell-extracellular matrix interactions. However, cell survival, apoptosis and anoikis also happen to implicate further mechanistic distinctions according to the specific tissue and/or cell type concerned. Incidentally, recent studies in a particular tissue, the human intestinal epithelium, have unearthed yet another layer of complexity in the regulation of these three cellular processes, namely the implication of differentiation state-specific mechanisms. Although our understanding of the molecular underpinnings of this new concept of differentiation state-distinct regulation of cell survival, apoptosis and/or anoikis is in its infancy, there is already evidence that such principle applies as well to cell types other than intestinal epithelial cells. Further studies on the differentiation state-specific regulation of these three cellular processes, either under normal or physiopathological situations, should prove crucial in increasing our understanding of pathologies which implicate a dysregulation of apoptosis and/or anoikis - such as cancer.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".