Effect of Different Treatments on Seed Germination Characteristics and Seedling Growth of Zania insignis
Bibliographic record
Abstract
With the seed of Zania insignis from TongDao,Hu'nan Province,the effects of seed pretreatment(A),hormone kinds(B),hormone concentration(C)and soaking time(D) on seed germination characteristics and seedling growth were studied by applying orthogonal test design.The results showed that the No.1 was the highest,the germination percentage,germination energy and germination index of which were 85%,85% and 35.56 respectively.The No.8 was the lowest,with the value of germination characters only 50%,36.6% and 7.77.Range analysis and variance analysis showed that hormone concentration was the most important factor for the germination percentage,germination energy and germination index.Each germination parameter of GA 3 treatment was better than that of NAA and IBA significantly.In the nine treatment testes,No.1was the best for the seedling growth.Comprehensive consideration,the best treatment was A 1B 1C 2D 2(dressed with dense sulfuric acid+GA 3+200 mg/L+2 h soaking time).
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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) | 0.001 | 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".