Evidence for epistasis: reply to Trouve <i>et al</i>.
Bibliographic record
Abstract
Abstract Salathé and Ebert (2003, J. Evol. Biol. 16: 976–985) have shown that the mean logarithmic fitness of Daphnia magna clones declined faster than linearly with increasing inbreeding coefficient F. They interpreted this result as evidence for synergistic epistasis. Trouve et al. (2004, J. Evol. Biol., doi: 10.1111/j.1420-9101.2004.00755.x) suggested that hybrid vigour could be an alternative explanation for this finding. We use a population genetic model to support the original claim that the marked deviation from linearity cannot be explained without epistasis. We further argue that the relevant reference population is the metapopulation and not the subpopulation. Taken together, we believe that synergistic epistasis between recessive deleterious alleles segregating in the D. magna metapopulation is the most likely explanation for the finding of Salathé and Ebert.
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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 | 0.014 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.032 | 0.058 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".