HARVEST INDEX OF PEA PLANT AND SOIL PROPERTIES INFLUENCED BY A TWO-YEAR AMENDMENT OF BIOCARBONS UNDER MUNICIPAL WASTEWATER IRRIGATION IN ARID CLIMATE
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
In this study, the influence of biochars, produced from cow manure and wood, on the harvest index of pea plants (Pisum sativum L.) and soil properties under groundwater and municipal wastewater irrigation was investigated. Biochars were applied at 5, 10 and 15 t ha -1 rates for two years. Yield biomass (pods) was higher under groundwater irrigation. As compared to control, amendment of biochar did not influence harvest index for both years, under irrigation treatments; however, as compared to wastewater irrigation, harvest index tended to be higher under groundwater irrigation. Soluble phosphorus level was higher in response to manure derived biochar under groundwater irrigation and nitrogen level was higher in response to lower rate of manure derived biochar under wastewater irrigation as compared to groundwater-irrigated soil. Under wastewater, macroaggregate stability was significantly increased within the soil as compared to groundwater irrigation, while; macroaggregates stability was observed in response of wood-derived biochar at higher rate under groundwater irrigation. Bacterial diversity was two-fold higher in the soil irrigated with groundwater as compared to the soil irrigated with wastewater.
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 | 0.000 | 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 it