Study on Effect of Water Immersion and Gibberellin Treatments on Seed Germination of Vitex negundo var. heterophylla
Bibliographic record
Abstract
Experiments on improving Vitex negundo var.heterophylla seeds germination were carried by different treatment methods,one was water immersion treatment for different days(1,2,3 d),the other was comprehensive treatment dealing seeds with 0.8‰ gibberellin for different hours(2,4,6 h) after the water immersion for different days(1,2,3 d).The results indicated that both treatment methods had obvious effect on seeds germination percentage,germinability and germinates index of Vitex negundo var.heterophylla.Water immersion treated for three days,seed germination rate(70.00%),germinability(65.33%) and germination index(22.01) improved significantly.However,effect of water immersion treatment for one days was not obvious.Comprehensive treatment had significant effects on seeds germination percentage,germinability and germinates index of Vitex negundo var heterophylla,especially in germination rate.Germinability and germination index of comprehensive treatment were not significant compared with water immersion treatment.Comprehensively considered,the method that water immersion for 2 days then disposed by 0.8‰ gibberellin for 4 hours was the best treatment,the germination percentage 87.33%,germinability 64.67% and germinates index 20.00.
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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".