Agro-economic Feasibility of Intercropped Systems of Radish and Cowpea-Vegetable Manured With Roostertree Biomass
Bibliographic record
Abstract
The association of crops presents as one of the cultivation practices to be used in the systems of vegetable crop production in the northeast Brazil semiarid, fertilized with biomass of spontaneous species of the Caatinga biome as green manure. Under this approach, a study was performed during the period from June to December 2013, in the research area of the Experimental Farm belonging to the Universidade Federal Rural do Semi-árido, Mossoró, RN (Brazil), to assess the feasibility of the agro-economic efficiency of the radish × cowpea-vegetable association manured with different amounts of roostertree biomass in semiarid environment. A randomized complete block design was used with four treatments and five repetitions. The treatments were composed of four biomass amounts of roostertree incorporated to the soil (10, 25, 40 and 55 t ha-1 on a dry basis). The highest agronomic and economic efficiencies of the intercropping of radish with cowpea-vegetable were obtained with the incorporation of 53 and 47 t ha-1 of roostertree biomass added to the soil. The roostertree spontaneous species of the Caatinga biome it is showed as an efficient green manure in the association of radish with cowpea-vegetable.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".