Bibliographic record
Abstract
[Objective]Effects of different fertilization and planting density on bitter gourd yield at different harvesting stages were studied to improve the yield and quality of bitter gourd in order to assist in increasing farmers' income.[Method]Using Cuizhongcui bitter gourd as test material,effects of nitrogen,potassium,phosphorus,and planting density on yield of bitter gourd were evaluated based on the optimum compound design 416-B.[Result]Nitrogen application rate was significantly positively correlated with bitter gourd yield at early harvesting stage.The influence degree of 3 factors on yield followed the following sequence:N K P.Planting density was significantly positively correlated with the accumulative yield of bitter gourd(y1)in 15 days.To achieve the highest accumulative yield of bitter gourd in 15 days,the optimal N,P,K application formula was N 304.80㎏/ha,P2O5 148.56㎏/ha,and K2O 351.75㎏/ha,with planting density of 29010 plants/ha.[Conclusion]Nitrogen fertilizer and planting density were the most predominant factors affecting yield rate of bitter gourd at early harvesting stage.
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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".