Influence of Planting Density on Yield and Ginsenoside Levels of<i>Panax quinquefolius</i>L.
Bibliographic record
Abstract
Field trials were established to determine the effects of fungicide treatment and seeding density on yield and ginsenoside concentration in roots of ginseng (Panax quinquefolius L.). The application of the fungicides metalaxyl and fosetyl-Al had no effect on plant stand or root weights. As seeding density increased from 50 seeds/m2 to 240 seeds/m2, the number of roots at harvest and total dry root weight increased, but average root size decreased. The increases were best described by nonlinear regressions using exponential rise to maximum equations or, in the case of mean dry weight per root, by hyperbolic and exponential decay equations. The total concentration of ginsenosides in roots was not affected by seeding density. The amounts of ginsenosides Re and Rb2 were slightly, but not significantly, increased as seeding density increased.
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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 | 0.001 |
| 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".