Facilitate Seed Germination of the Golden Shower Tree (Cassia fistula) in vitro Using TiO2 Nanoparticles and Scarification Treatments
Bibliographic record
Abstract
The main propagation method of Cassia fistula is sowing seeds. The seed germination is usually low because of its impermeable hard coat. Therefore, this experiment evaluated the effects of TiO2 nanoparticles and scarification methods on seed germination and seedling growth in vitro condition. The tree seeds were treated with, hot water, H2SO4 (36N), and mechanical scarification and culture on ¼ MS salt mixture. The medium was supplemented with different concentrations of TiO2 nanoparticles. The results showed that the highest percentage and rate of germination was recorded in seeds treated with mechanical scarification. The highest shoot and root dry weight was recorded for seeds treated with mechanical scarification and grown on MS media supplemented with 1.5 mg/ml TiO2 nanoparticles. TiO2 nanoparticles did not show any significant effects on the percentage and rate of germination. Different growing soil mixtures had significant effects on the growth of the ex vitro transferred plantlets. Coco peat and peat moss mixture (1:1) was found to be more effective in increasing the number of leaves and root length of the seedlings.
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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 | 0.000 | 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".