THREE-GENE IDENTITY COEFFICIENTS DEMONSTRATE THAT CLONAL REPRODUCTION PROMOTES INBREEDING AND SPATIAL RELATEDNESS IN YELLOW-CEDAR,<i>CALLITROPSIS NOOTKATENSIS</i>
Bibliographic record
Abstract
Asexual reproduction has the potential to promote population structuring through matings between clones as well as through limited dispersal of related progeny. Here we present an application of three-gene identity coefficients that tests whether clonal reproduction promotes inbreeding and spatial relatedness within populations. With this method, the first two genes are sampled to estimate pairwise relatedness or inbreeding, whereas the third gene is sampled from either a clone or a sexually derived individual. If three-gene coefficients are significantly greater for clones than nonclones, then clonality contributes excessively to genetic structure. First, we describe an estimator of three-gene identity and briefly evaluate its properties. We then use this estimator to test the effect of clonality on the genetic structure within populations of yellow-cedar (Callitropsis nootkatensis) using a molecular marker survey. Five microsatellite loci were genotyped for 485 trees sampled from nine populations. Our three-gene analyses show that clonal ramets promote inbreeding and spatial structure in most populations. Among-population correlations between clonal extent and genetic structure generally support these trends, yet with less statistical significance. Clones appear to contribute to genetic structure through the limited dispersal of offspring from replicated ramets of the same clonal genet, whereas this structure is likely maintained by mating among these relatives.
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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 | 0.001 | 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 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".