Bibliographic record
Abstract
More often than not, life on Earth exists in an environment that is both comfortable yet competitive. It is comfortable in that molecular construction materials are available in a fluid medium at a suitable temperature for self-assembly and appropriate functionality. It is competitive in that cell populations are unregulated and cell design is subject to random changes, permitting better-adapted designs to flourish at the expense of less-adapted designs. Cells have no choice but to go forth and multiply if their design is to survive: individual cells must duplicate their blueprint for use by successive generations and they must grow, although not without limit. The maximum size to which an individual cell may grow within a sustainable population may be influenced by many factors, including the time scale for the transport of nutrients from external sources and the surface stresses on the cell’s membranes and walls, which generally scale with cell size. Further, as cell design becomes more complex for advanced or specialized cells, the functionality and perhaps structural arrangements of its components may be forced to change during its lifetime, which in turn requires the cell to develop means of regulating its functionality . In this chapter, we describe the gross structural changes that a cell undergoes during the cell cycle, and the mechanism by which its blueprint is duplicated. Section 12.1 contains a survey of the main events of prokaryotic and eukaryotic cell cycles, which is then quantitatively examined for bacteria and simple eukaryotes (such as green algae) in Section 12.2. This section includes influences on the cell cycle that have a physical origin, such as mechanical stresses and diffusion. Although the simplest models portray the cell cycle as having a doubling time with division into identical daughter cells, in reality both doubling time and daughter size are distributed around a mean; asymmetry and asynchrony of the cycle are the subjects of Section 12.3. Two successive sections of this chapter (12.4 and 12.5) are devoted to microscopic issues in the cell cycle, namely the forces and mechanisms of DNA replication and segregation; additional biomolecular aspects of transcription are treated later in Section 13.4. For an introduction to the mechanical aspects of cell growth in the context of tissues, see Shraiman (2005).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.055 | 0.052 |
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".