Influence of Chemical Pretreatments on the Germination of Ficus Pumila Seeds
Bibliographic record
Abstract
we has studied on the influence of the chemical pretreatments of different concentration of HNO3,KNO3,GA solutions,and their mixed solutions on the frequency of seed germination.The results were showed as follows: there are significant differences on germination percentage,germination energy and germination index of Ficus pumila seeds from different plants.The germination of Ficus pumila seeds were improved by the pretreatment of proper soaking concentration of HNO3,KNO3 and GA solution.The best concentration of the comprehensive treatment was 37.78 mmol/L of HNO3 and 30 mg/L of GA,compared with the control group,which increased 2.27 times in germination percentage,11.25 times in germination energy and 4.72 times in germination index,so its germination time shortens 5-6 days.
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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) | 0.001 | 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".