Effects of Different Priming Treatments on Germination of Wild Eggplant Rootstock Solanum Torvum Seeds
Bibliographic record
Abstract
Used different treatments to prime Solanum Torvum seeds to study the effect of different priming treatments on germination and statisted seeds germination percentage at 20th day.The results showed that:the priming treatment of 0.50% NaNO3 significantly enhanced germination index and germination rate of Solanum Torvum seeds,and the priming treatment of 0.50% MnCl2 also promoted germination index of Solanum Torvum seeds,but had no influence on germination rate.The priming treatment of 300 mg/kg gibberellins increased Solanum Torvum seeds germination significantly.If gibberellins concentration was too high or too low,it even could inhibit Solanum Torvum seeds germination.This study established a new germination method:hydration-pregerminating-dehydration,which increased germination index and germination rate of Solanum Torvum seeds pre-germinated 6 days,and the effect could keep 2 months in normal temperature and more than 3 months in low temperature.
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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) | 0.001 | 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 | 0.001 |
| 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".