The development of microsatellite DNA markers for genetic analysis in Douglas-fir
Bibliographic record
Abstract
The microsatellite motifs AG, AC, and ATG were found to be the most abundant in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and several other conifer tree species among di-, tri-, and tetra-nucleotide simple sequence repeats (SSR). Colonies containing AG, AC, and ATG repeats were selected from enriched genomic libraries of Douglas-fir, and 603 were sequenced. Polymerase chain reaction (PCR) primers were designed from flanking sequences in 102 of the SSR clones, of which 50 primer pairs (for 10 AC-repeat microsatellites and 40 AG-repeat microsatellites) produced robust amplification products. Variability was confirmed with 24 unrelated Douglas-fir trees and Medelian segregation with 33-66 progeny from 3 full-sib populations. Forty-eight of the 50 loci were polymorphic, with a mean of 7.5 alleles per locus. Allele sizes ranged from 73 to 292 base pairs. Allele frequencies for the 48 polymorphic loci varied from 0.017 to 0.906 with mean allele frequency of 0.250. Expected heterozygosities among the polymorphic loci varied from 0.174 to 0.926, with a mean of 0.673. Additional, high molecular weight PCR products were amplified by some of the primer pairs, but they did not interfere with the scoring of alleles. Most of the Douglas-fir primer pairs also amplified SSR-containing loci in other conifer species.
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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 | 0.001 |
| 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".