COMPARATIVE ANALYSIS OF DAMD, ISSR AND SCOT MOLECULAR MARKERS ON CRYOPRESERVED LUDISIA DISCOLOR AXILLARY BUDS
Bibliographic record
Abstract
Ludisia discolor, a jewel orchid is the only species found under its genus (Ludisia). This wild orchid is well known for its striking foliage and its medicinal benefits. Since the population of this valuable species is becoming scarce, therefore protecting this orchid is crucial. Cryopreservation is a practicable long-term germplasm conservation approach. The genetic material is stored at freezing temperature using liquid nitrogen. In this study, V cryo-plate method was developed using L. discolor axillary buds using optimum conditions. For the screening of somaclonal variation, 3 weeks old treated (cryopreserved and non-cryopreserved) explants were utilized in comparison with the stock cultures as a control. The genetic stability was assessed using a total of twenty (20) DAMD, twenty (20) ISSR, and ten (10) SCoT molecular markers. The somaclonal variation detected in cryopreserved explant using DAMD, ISSR, and SCoT molecular markers were 12.5, 4.17, and 10.53% respectively. However, somaclonal variation was also detected in non-cryopreserved explants using DAMD, ISSR, and SCoT at 6.15, 5.77, and 10%, respectively. Hence, SCoT was chosen to be precise than the other two molecular markers (DAMD and ISSR).
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 | 0.000 | 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 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".