Isolation, characterization, and cross-species utility of microsatellites in yellow cedar (<i>Chamaecyparis nootkatensis</i>)
Bibliographic record
Abstract
Chamaecyparis nootkatensis is an ecologically and economically important conifer of the north Pacific coastal forests. To aid in studies of clonal structure and genetic differentiation of this and related species, we isolated and characterized microsatellites from C. nootkatensis. A microsatellite-enriched library yielded 75 repeat-containing sequences for which primer pairs were designed. Only five showed reliable amplification and polymorphism, with an average of 13.7 alleles/locus and a mean expected heterozygosity of 0.592. In progeny tests with four families, few null alleles were directly detected and loci segregated according to Mendelian expectations. However, in one primer pair, high heterozygote deficiency was observed, suggesting the presence of a null allele. The ability of primer pairs to cross amplify was tested on 18 species of the Cupressaceae sensu lato; three primer pairs yielded polymorphic loci in Cupressus and Juniperus species, but not in other Chamaecyparis species. This also supports recent findings of a closer affinity of C. nootkatensis with Cupressus over other Chamaecyparis species.
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".