MHC class IIB additive and non‐additive effects on fitness measures in the guppy <i>Poecilia reticulata</i>
Bibliographic record
Abstract
The genetic architecture of fitness at the class IIB gene of the major histocompatibility complex (MHC) in the guppy Poecilia reticulata was analysed. Diversity at the MHC is thought to be maintained by some form of balancing selection; heterozygote advantage, frequency-dependent selection or spatially and temporally fluctuating selection. Here these hypotheses are evaluated by using an algorithm that partitions the effect of specific MHC allele and genotypes on fitness measures. The effect of MHC genotype on surrogate measures of fitness was tested, including growth rate (at high and low bulk food diets), parasite load following a parasite challenge and survival. The number of copies of the Pore_a132 MHC allele was inversely related to infection by Gyrodactylus flukes and it appeared to be positively related to faster growth. Also, genotypes combining the Pore_a132 or other relatively common alleles paired with rare MHC alleles produced both advantageous and detrimental non-additive effects. Thus, the genetic architecture underlying fitness at the MHC is complex in the P. reticulata.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".