Intercropping of Pearl millet + Cowpea as Rainfed Fodder Crops with Aonla based Agri-horti-system
Bibliographic record
Abstract
An experiment was conducted to utilize interspaces of grownup (13 years old) aonla plantation with rainfed fodder crop combinations to optimize forage and fruit production. The aonla fruit production was not influenced with intercropping of fodder crops under rainfed and produced fruit yield of 13.65 t/ha. Pearlmillet (multicut) + cowpea produced significantly higher yield 21.6 t green fodder as compared to 18.4 t green fodder obtained from Pearlmillet (single cut) + cowpea. Fodder production in association with tree was also higher (20.75 t green fodder) as compared to sole crop. Higher B: C ratio 2.48:1 and 4.02:1 respectively of aonla based fodder production was recorded in 1st year and 2nd year when aonla trees were intercropped with Pearlmillet multicut+cowpea. The soil nutrient build up was also noticed in fodder intercropped in association with aonla tree.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".