Costs and benefits of genetic heterogeneity within organisms
Bibliographic record
Abstract
An increasing number of studies have recently detected within-organism genetic heterogeneity suggesting that genetically homogeneous organisms may be rare. In this review, we examine the potential costs and benefits of such intraorganismal genetic heterogeneity (IGH) on the fitness of the individual. The costs of IGH include cancerous growth, parasitism, competitive interactions and developmental instability, all of which threaten the integrity of the individual while the potential benefits are increased genetic variability, size-specific processes, and synergistic interactions between genetic variants. The particular cost or benefit of IGH in a specific case depends on the organism type and the origin of the IGH. While mosaicism easily arise by genetic changes in an individual, and will be the more common type of IGH, chimerism originates by the fusion of genetically distinct entities, and is expected to be substantially rare in most organisms. Potential conflicts and synergistic effects between different genetic lineages within an individual provide an interesting example for theoretical and empirical studies of multilevel selection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".