Land Suitability Study in Ultisols for Soybean Based on Soil Fauna
Bibliographic record
Abstract
Evaluation of land suitability for soybean by involving the presence and biodiversity of soil fauna has been conducted. The research was done on thecenter of soybean plantations in Ultisols soils in Banten, Lampung, and Lahat (south Sumatera) Provinces. The objective of research was to determine the interaction between soil fauna diversity in Ultisols soil and productivity of soybean. The research used a Survey Method. Every location was divided into three categories of vegetation performance, such as, less vegetation, average vegetation, and very fertile vegetation with two replicates. The chemical, physical, and biological properties of soils from every unit sampling were analyzed. The results showed that nutrient and chemical properties of soil which directly influenced the growth and production of soybean was P-potential, P-available, K-available, B (Boron), Ca and pH; the physical properties were pores drainage, pores rapid drainage, soil water content, and soil permeability. The presence of earthworm did not have direct effect to soybean, except as the 3th between variables, meaning that the presence of earthworms affected soil physical properties, soil physical properties affected nutrient availability, nutrient availability affected the biomass and yield of soybean.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".