Relationships among some pines from subgenera Pinus and Strobus revealed by nuclear EST-microsatellites
Bibliographic record
Abstract
Genetic relationships among 12 taxa from subgenera Pinus and Strobus were studied through fourteen microsatellite markers, previously developed for Pinus taeda. To our knowledge, this is the first comparative study of pines using nuclear EST-microsatellites (EST-SSRs). The total number of detected alleles in all investigated taxa was 72 (5.14 in average). The numbers of alleles per locus and PIC values for estimated markers ranged from 3 to 7, and from 0.43 to 0.81, respectively. Presented results are in accordance with majority of previous genetic investigations and infrageneric classification of genus Pinus up to the sectional level, while subsectional position of some species has still not dismissed, especially regarding relict ones. According to nuclear EST-SSRs, Pinus heldreichii is in early-diverging position within subsection Pinaster and shows the greatest closeness with P. halepensis, while Pinus peuce doesn't have basal position within subsection Strobus being more close to P. strobus than to P. wallichiana. Furthermore, the closest connections in subsection Pinus were found between two Pinus nigra subspecies (dalmatica and nigra) as well as between P. sylvestris and P. mugo.
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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 | 0.001 |
| 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) | 0.001 | 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".