<scp>polygene</scp>: Population genetics analyses for autopolyploids based on allelic phenotypes
Bibliographic record
Abstract
Abstract Polyploidy has appeared in almost every ancestral plant lineage, and in extant species, occurs frequently. When present, polyploidy presents problems for genetic data analysis, which are caused by both genotypic ambiguities and double‐reduction. To address these problems, we developed a new software package, polygene , which enables the estimation of genotypic frequencies for a number of polysomic inheritance models. Specifically, polygene obtains posterior probabilities for genotypes hidden within allelic phenotypes. Comprehensive modes of genetic analyses are provided by polygene, which include genetic diversity analysis, tests for allelic phenotypic or genotypic distributions, linkage disequilibrium and genetic differentiation, genetic distance analysis, principal coordinates analysis, hierarchical clustering analysis, individual inbreeding coefficient estimation, individual heterozygosity index estimation, population assignment, pairwise relatedness estimation, parentage analysis, analysis of molecular variance and Bayesian clustering. polygene enables easy and convenient allelic phenotype‐ or genotype‐based analysis for both autopolyploids and diploids. polygene will thus facilitate molecular ecology research involving autopolyploids.
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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".