Effects and Drought-Resistances Evaluation of Drought Simulate by PEG-6000 on Agropyron mongolicum Keng Seed Germination
Bibliographic record
Abstract
The experiment was conducted to estimate the seed germination characteristics and drought tolerance in 7 different source accessions of Agropyron mongolicum by simulated drought stress with different concentrations of PEG-6000.The results showed that the relative germination rate,relative germination energy,relative drought resistant index,relative vitality index,relative seedling length and relative seedling weight of A.mongolicum all decreased significantly with the increased of PEG-6000 concentration.Low concentrations of PEG could promoted radicle lengths,but high concentrations of PEG could restrained radicle length.The germination rate,germination energy,seedling length and radicle length had significant difference,but drought resistant index,vigor index and seedling weight hadn’t significant difference among 7 accessions.According to the above seven indicators,with subordinate function,the drought-resistance sequence of 7 accessions from high to low was: No.3 No.7 No.2 No.4 No.6 No.1 No.5.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".