Identification and Genetic Relationship Analysis of <i>Torreya</i> Based on nrDNA ITS Sequence
Bibliographic record
Abstract
In order to evaluate the identification ability of nrDNA ITS sequences on Torreya , this study used ITS sequence and four different analysis methods (BLAST, K2P genetic distance, SNP analysis, NJ tree) to identify species of Torreya , and established phylogenetic trees to discuss their phylogenetic relationships. The results showed that the length of 48 ITS sequences was 1 095 bp~1 105 bp, the average intraspecies genetic distance was 0.001 6 and the average interspecies genetic distance was 0.015 0. At the species level, BLAST alignment and NJ tree had the highest efficiency in Torreya . The SNP loci analysis could effectively identify T. grandis cv . ‘ Merrillii ’ and T. grandis . The analysis of genetic relationship showed that all the other species of Torreya were single-line branches, but the quince tree of T. yunnanensis and T. fargesii were clustered into a cluster in the ML tree, indicating that the two were closely related. This provided evidence for the nuclear genome sequence proposed the incorporation of T. yunnanensis and T. fargesii . This study showed that ITS sequence could be used as a DNA barcode for the identification of Torreya , and providing reference for the identification and systematic relationship of Torreya.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".