Genealogical Relationship among Members of Selection and Production Populations of Yellow Cedar (Callitropsis nootkatensis [D. Don] Oerst.) in the Absence of Parental Information
Bibliographic record
Abstract
We used DNA fingerprinting and pedigree reconstruction to determine the genetic relationship among members of 3 yellow-cedar (Callitropsis nootkatensis [D. Don] Oerst.) selection populations in the absence of their parental genotypes. Selection population members consisted of the tallest individuals within seedling crops originated from natural stand seed collected from multiple seed donors covering wide areas within 3 distinct locations (phenotypic mass selection). Pairwise relative kinship estimates indicated the presence of extensive coancestry among the selected seedlings, and pedigree reconstruction grouped each selection members into multiple full-sib families of different sizes (1-10) nested within several half-sib families (19-21). The "STRUCTURE" program (Pritchard JK, Stephens M, Donnelly P. 2000. "Inference of population structure using multilocus genotype data." Genetics. 155:945-959.) provided a pictorial classification of the 3 selection populations and grouped their individuals into multiple cohorts (9-10). The STRUCTURE program's results corresponded with that of the pedigree reconstruction, indicating that members of the selection populations originated from a subset of the seed donors forming the natural stand seed collections. The species' silvics, reproductive biology, methods of natural stand seed collection and seedling production, and the high selection intensity applied to form the selection populations contributed to limiting the selection to a subset of the original donor trees. The associated buildup of coancestry in selection and production populations is expected to result in inaccurate estimation of genetic parameters and an unintentional reduction in genetic diversity in reforestation stocks.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".