Economics of potassium fertiliser application in rice, wheat and maize grown in the indo-gangetic plains
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
Kaushik Majumdar, Anil Kumar, Vishal Shahi and T. Satyanarayana International Plant Nutrition Institute (IPNI)-South Asia Program, Gurgaon, Haryana, India M. L. Jat and Dalip Kumar International Maize and Wheat Improvement Centre (CIMMYT), NASC Complex, Pusa, New Delhi, India Mirasol Pampolino International Plant Nutrition Institute (IPNI)-South East Asia Program, Penang, Malaysia Naveen Gupta Punjab Agricultural University, Ludhiana, Punjab, India Vinay Singh Dr. B. R. Ambedkar University, Agra, Uttar Pradesh, India B. S. Dwivedi and M. C. Meena Indian Agricultural Research Institute (IARI), Pusa, New Delhi, India V. K. Singh Project Directorate for Farming Systems Research, Modipuram, Meerut, India B. R. Kamboj Cereal Systems Initiative for South Asia (CSISA), IRRI-CIMMYT, Haryana Hub, Karnal, India H. S. Sidhu Borlaug Institute for South Asia (BISA), CIMMYT, Ladowal, Punjab, India and Adrian Johnston International Plant Nutrition Institute (IPNI), Saskatoon, Saskatchewan, Canada Indian J. Fert., Vol. 8 (5), pp.44-53 (10 pages)
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 | 0.000 |
| 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 | 0.001 |
| 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