Penerapan Sistem Pertanian Organik dengan Aplikasi Pupuk Organik Cair Urin Kelinci pada Padi Sawah
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 it