Preliminary Study on Morphological and Physiological Indicators of Different Perilla Varieties
Bibliographic record
Abstract
Through comparing agricultural characteristics and physiological indexes of breeding variety purple perilla with left home-perilla and Baisu Perilla.The results showed that agricultural characteristics and physiological indexes of breading variety purple perilla was different significant from that of Baisu and left home Perilla.The plant height and number of branches and inflorescence were more than that of left home perilla and Baisu,and chlorophyll,soluble sugar and soluble protein,crude fat content of Perilla were higher than that of left home perilla and Baisu,but proline content was less than that of left home perilla and Baisu.According to comparing the three varieties fertility status,breeding new variety Perilla belonged to late maturity variety,left home Perilla belonged to mid-maturity variety,and Baisu belonged to early maturity variety.
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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".