The mutational hazard hypothesis of organelle genome evolution: 10 years on
Bibliographic record
Abstract
Why is there such a large variation in size and noncoding DNA content among organelle genomes? One explanation is that this genomic variation results from differences in the rates of organelle mutation and random genetic drift, as opposed to being the direct product of natural selection. Along these lines, the mutational hazard hypothesis (MHH) holds that 'excess' DNA is a mutational liability (because it increases the potential for harmful mutations) and, thus, has a greater tendency to accumulate in an organelle system with a low mutation rate as opposed to one with a high rate of mutation. Various studies have explored this hypothesis and, more generally, the relationship between organelle genome architecture and the mode and efficiency of organelle DNA repair. Although some of these investigations are in agreement with the MHH, others have contradicted it; nevertheless, they support a central role of mutation, DNA maintenance pathways and random genetic drift in fashioning organelle chromosomes. Arguably, one of the most important contributions of the MHH is that it has sparked crucial, widespread discussions about the importance of nonadaptive processes in genome evolution.
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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".