Paternity analysis with microsatellites in a Danish <i>Abies nordmanniana</i> clonal seed orchard reveals dysfunctions
Bibliographic record
Abstract
A paternity analysis using five microsatellite markers was conducted in a Danish clonal seed orchard with 13 Abies nordmanniana (Stev.) Spach clones. The purpose was to investigate potential seed-orchard dysfunctions, with special emphasis on nonequal pollen contributions and selfing. Male paternity was found for 232 seedlings germinated from seeds collected on three ramets, each of eight clones, and the relative contribution of each clone to the gene pool of male gametes was calculated. Furthermore, 49 ramets were genotyped to check for erroneous grafting. The effect of an unbalanced male contribution was quantified by means of two measures: (1) the status number (NS), which reflects buildup of coancestry in the seed-orchard crop as a result of a low number of clones and an unequal male contribution, and (2) the asymptotic variance effective population number (Ne(v)). The contributions by pollen donors from the 13 clones were highly skewed. Three clones were fathers to more than 75% of the progenies, while making up only 24% of the ramets in the seed orchard. Four clones sired no progenies at all. The unequal contribution on the male side corresponded to NS = 4.2 and Ne(v) = 5.8. Some selfing was observed, which may give rise to concern if clonal seed orchards with few clones are established. The estimated maximum pollen contamination from outside the seed orchard was 4.3%. No graftinglabelling errors were identified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".