GENETIC VARIATION AND DNA REPLICATION TIMING, OR WHY IS THERE LATE REPLICATING DNA?
Bibliographic record
Abstract
Mutation rates vary significantly within the genome and across species. Recent studies revealed a long suspected replication-timing effect on mutation rate, but the mechanisms that regulate the increase in mutation rate as the genome is replicated remain unclear. Evidence is emerging, however, that DNA repair systems, in general, are less efficient in late replicating heterochromatic regions compared to early replicating euchromatic regions of the genome. At the same time, mutation rates in both vertebrates and invertebrates have been shown to vary with generation time (GT). GT is correlated with genome size, which suggests a possible nucleotypic effect on species-specific mutation rates. These and other observations all converge on a role for DNA replication checkpoints in modulating generation times and mutation rates during the DNA synthetic phase (S phase) of the cell cycle. The following will examine the potential role of the intra-S checkpoint in regulating cell cycle times (GT) and mutation rates in eukaryotes. This article was published online on August 5, 2011. An error was subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected October 4, 2011.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".