Assessment of the Agronomic Value of Organic Fertilizer Made of Composted Sludge
Bibliographic record
Abstract
The study presents data on changes in the chemical composition of sludge in Astana (Republic of Kazakhstan) during composting with the addition of wheat straw and microbial biological preparations.The purpose of this study was to evaluate the agronomic value of sludge compost as a fertilizer.The specific hypotheses tested in this study were: (1) the addition of different biological preparations will improve the quality of the compost, enhancing its nutrient content (nitrogen, phosphorus, potassium), and (2) the incorporation of wheat straw will reduce nitrogen losses during composting by increasing the carbon-to-nitrogen ratio.Quantitative changes in the chemical components of compost from a mixture of sludge and wheat straw during composting were studied.The pH of the sludge increased during the first 10 days of composting and then decreased.In almost all samples, the amount of total phosphorus and potassium increased up to 2 times during composting.Losses reached up to 35% of the initial nitrogen, as a result of nitrogen volatilization.The addition of straw helped to reduce nitrogen losses during the active phase by increasing the carbon-to-nitrogen ratio in the initial mixtures.
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.
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".