Effect of Na_2SeO_3 on Physiological Characteristics of Rice Seed Germination under PEG Stress
Bibliographic record
Abstract
In this study,effects of 0 μmol /L,0. 5 μmol /L,1. 0 μmol /L,1. 5 μmol /L and 2. 0 μmol /L Na2SeO3 on physiological characteristics of rice seed germination under PEG stress were explored. The results showed that 0. 5 μmol /L and 1. 0 μmol /L Na2SeO3treatment significantly improved seed germination rate compared with the control. α-Amylase activity,soluble sugar and soluble protein content in germinating seeds were increased,but free amino acid content was reduced. Also,radical root activity and root length were increased.In contrast,2. 0 μmol /L Na2SeO3 exerted opposite effects on seed germination. Obviously,low concentrations of Na2SeO3 treatment can alleviate PEG stress,but high concentrations aggravated the adverse effects of PEG stress on seed germination.
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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".