Mutation Load: The Fitness of Individuals in Populations Where Deleterious Alleles Are Abundant
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many multicellular eukaryotes have reasonably high per-generation mutation rates. Consequently, most populations harbor an abundance of segregating deleterious alleles. These alleles, most of which are of small effect individually, collectively can reduce substantially the fitness of individuals relative to what it would be otherwise; this is mutation load. Mutation load can be lessened by any factor that causes more mutations to be removed per selective death, such as inbreeding, synergistic epistasis, population structure, or harsh environments. The ecological effects of load are not clear-cut because some conditions (such as selection early in life, sexual selection, reproductive compensation, and intraspecific competition) reduce the effects of load on population size and persistence, but other conditions (such as interspecific competition and load on resource use efficiency) can cause small amounts of load to have strong effects on the population, even extinction. We suggest a series of studies to improve our understanding of the effects of mutation load.
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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 | 0.001 | 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 it