Nepalese Landraces of Sponge Gourd for the Production of Tender Fruits
Bibliographic record
Abstract
Evaluation of landraces is necessary for better management of agricultural biodiversity on- farm. The objective was to evaluate the farmers named landraces of sponge gourd that are being maintained on-farm for tender fruit production. A total of 21 sponge gourd landraces collected from six districts of Nepal were evaluated in a randomized complete- block design with three replications at Agriculture Research Station, Malepatan, Pokhara, Nepal. These landraces were significantly (p = 0.05) different for first harvest days (p = 0.05) and fruit yield per plant (p = 0.05), highly significant (p < 0.01) for last harvest days, fruit-skin thickness, flesh thickness, fruit length, fruit perimeter, fruit weight and fruit number. Variation for tender fruits among these landraces can be utilized for improving the genotypes of sponge gourd as well as for long-term production in diverse environments.
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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".