Bibliographic record
Abstract
Organic products are grown under a system of agriculture without using chemical fertilizers and pesticides, with an environmentally and socially responsible approach, and provide healthy food. It is developing rapidly and is practised in more than 120 countries. In 2022-23, the total area under the organic certification process (registered under the National Programme for Organic Production) is 10.17 million ha. This includes 5.39 million ha of cultivable area and another 4.8 million hectares for wild harvest collection. Madhya Pradesh has covered the most significant area under organic certification. In contrast, India produced around 2.9 million MT of certified organic products, which include all varieties of food products, namely Oil Seeds, fibre, Sugar cane, Cereals and millets, Cotton, Pulses, Aromatic and Medicinal Plants, Tea, Coffee, Fruits, Spices, Dry Fruits, Vegetables, Processed foods etc. The production is not limited to the edible sector; it produces organic cotton fiber, functional food products, etc. Among different states, Madhya Pradesh is the largest producer. In terms of exports, the total value was 0.31 million Mt. The organic food export realisation was around Rs. 5525.18 Crore (708.33 million USD). Products are exported to the USA, European Union, Canada, Great Britain, Switzerland, Turkey, Australia, Ecuador, the Korean Republic, Vietnam, Japan, etc. The objectives of organic farming ensure that food production has high nutritional value in adequate quantities and preserves and enhances the long-term fertility of soils.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".