Penerapan Sistem Pertanian Organik dengan Aplikasi Pupuk Organik Cair Urin Kelinci pada Padi Sawah
Bibliographic record
Abstract
The Ngudi Tani farmer group is one of the farmer groups in Bobosan Village, North Purwokerto District, Banyumas Regency. The rice fields in the Bobosan village area have irrigation system and the water is always available throughout the year, however rice farming has not been applied environmentally friendly agricultural system yet. Liquid Organic Fertilizer (LOF) of urine rabbit with quince bengal fruit could apply as substitution of fertilizer and pesticide synthetics.The purpose of this service activity was to increase understanding and knowledge about organic farming systems with the application of LOF in lowland rice and how to make rabbit urine LOF. Methods of activities were carried out through counseling and training related to LOF application in rice fields and makes use of rabbit urine LOF. The rice field plot was focused on the appropriate way of working and techniques in supporting rice production through the application of rabbit urine LOF. Counseling, training, demonstration plots and rabbit livestock introduction is successful even though not to all members of the farmer groups. The knowledge and skills of farmers have increased regarding rabbit livestock and processing of urine into liquid organic fertilizer and its application to lowland rice. The introduction of rabbit urine LOF in lowland rice cultivation has been responded positively by some members of farmer groups and farmers have understood the procedure for processing rabbit urine waste into liquid organic fertilizer and its application in rice plants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.007 |
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".