Medicinal Plants: Trade and Commerce Opportunities with India
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
About 5,000 plant species have been documented for medicinal value and phyto-chemically studied. Of these, 1,100 are used in different systems of medicine, 600-700 are used in indigenous industries, but only about 150 have been commercially exploited. Besides domestic use, export potential of these plants is huge and given a quality upgadation of such drugs, competitiveness and globalization is ensured. There is, however need for doing scientific work on their pharmacology, phytochemisty and clinical experiments to develop the export potential fully. Important plant species being utilized at present, their world prices, and other potential species have been listed. Shift towards use of herbal drugs worldwide has been noted. There is good scope in developing this sector. Trade and commerce requirements relating to export and marketing in various foreign marketing ego Canada, Hungary, France, UK, USA have been discussed with a view to developing trade in these countries in medicinal products. Various measures, which handicap expansion, have been pointed out. These are: agricultural practices like harvesting and propagation, processing high yield varieties, quality control, marketing, training of personnel, equipment and knowledge about latest advances in technology etc. where efforts need to be focussed.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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