Evaluation About the Seed Yield Per Fruit of Cucumber Germplasm Resources and the Correlation Research of the Mainly Fruit Traits in Cucumber
Bibliographic record
Abstract
In this study,the seed yield per fruit and the fruit traits of 50 accessions of different types of cucumber( Cucumis sativus L.) were tested,and correlation and path analysis with characteristics of cucumber was carried out. The results showed that there were obvious variances of the seed yield per fruit in different varieties of cucumber germplasm,swinging in the range of 0. 5- 7. 9 g. The output of five accessions was more than 6. 2 g and 5 accessions was less than 1. 0 g. The order of 7 related traits influence on the seed yield per fruit was as follows: number of seed per fruit fruit chamber diameter hundred-seed weight per fruit weight seed length seed wide fruit chamber length. Multiple regression analysis and Path analysis both showed number of seed per fruit and hundred-seed weight were the major factors to affect the seed yield per fruit,and the direct path coefficient were 0. 908、0. 363,respectively. In addition,between the four ecological types,per fruit seed production variance analysis was not significant.
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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 | 0.001 | 0.001 |
| 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".