Integrated Agriculture Production Systems for Meeting Household Food, Fodder and Fuel Security
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
Agriculture including crop production and animal husbandry provides for the food, fodder, and fuel needs in rural regions of many countries such as India. Using the knowledge pertinent to complex mixed cropping-livestock systems at the village level, the goal of this study is to develop a rational method for crop selection, such that the capacity for production of food, fodder and biomass fuel can be examined under various cropping patterns. An agricultural survey is carried out in November 2007 for three villages located in the dryland agro-ecozone of Karnataka State, India. Various demands, including human food energy and protein requirements, and constraints, including land area, are modeled for optimal cropping pattern. A clear recommendation of the study is that a substantial shift in village-wide area planted to cereal crops, in all cases over 50%, is necessary to satisfy human and livestock demands. Additionally, there are visible and growing population pressures on the resources in the dryland, semi-arid regions of India, and these strategies will need to be supplemented by improved agronomic practices directed toward increased productivity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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