Effect of Different Moisture Content on Seed Vigor of Coix lacryma-jobi L
Bibliographic record
Abstract
With artificial aging methods,the effects of different moisture contents on seed vigor of Coix lacryma-jobi L.,Liao Coix No.1 were studied.The results showed that the seed vigor would keep at a relatively higher level when the moisture content of Liao Coix No.1 seeds decreased from 16.94% to 14.89%.After artificial aging,the germination rate,germination index,the contents of soluble protein and soluble sugar of Liao Coix No.1 seeds with 14.89% moisture content entirely reached the maximum value.Meanwhile,the activities of amylase and POD were also at the relatively higher levels.On the contrary,the electric conductivity and the MDA content of Liao Coix No.1 seeds kept at the lowest level at the same condition of moisture content,and the decrease of dehydrogenase activity was the least as well.Based on the above results,it could be inferred that for the long-term preservation of Coix lacryma-jobi L.seeds to keep seeds at a higher vigor,an optimal moisture content was one of the most important factors.
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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) | 0.000 | 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 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".