The Assessment of Soil Quality Index for Paddy Fields with Indicator Biology in Jatipurno Districts, Wonogirl
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Bibliographic record
Abstract
Increased rice needs in an extensive use of paddy fields in the Jatipurno, Wonogiri. Managing rice fields can reduce soil quality. Proper management can improve soil quality, Jatipurno has management such as organic, semi-organic and inorganic paddy field management which have a real effect on soil quality. Assessment of soil quality is measured by physical, chemical and biological indicators, where each factor has a different effect. The chemical indicators are often used as the main indicators for determining soil quality, whereas every parameter has the opportunity to be the main indicator. So, biological indicators can play indicators. The main indicators are obtained from the correlation test (p-values ≤ 0,05 - < 0,01) and Principal Component Analysis with high value, eigenvalues > 1 have the potential to be used as Minimum Data Sets. The result is biological can be able to use as the Minimum Data Set such as microbial carbon biomass, respiration, and total bacterial colonies. The Soil Quality Index (SQI) of various paddy management practices shows very low to low soil quality values. The management of organic rice systems shows better Soil Quality Index with a score of 0,20 compared to other management. The practice of organic rice management shows that it can improve soil quality.
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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) | 0.000 | 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 | 0.001 | 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 it