A Comparative Study of Profitability of Selected Pharma Companies of India
Bibliographic record
Abstract
The Indian pharmaceutical industry is growing rapidly in the number of production, value, quantity, units and there are two main things that appear to conform to the story of the full growth of the Indian economy. Second, there has been a major change in the very basic system of pharmaceutical business in India. By issuing a patent ordinance, India fulfills WTO's commitment to identify foreign product patents from January 1, 2005, the culmination of the 10-year process. In this new scenario, Indian pharmaceutical manufacturers will not be able to manufacture patented drugs, which they have been doing for a long time, though by another process. This study has been done for important evaluation of India's pharmaceutical industry. This study focus on to analyse the profitability of the selected pharmaceutical companies of India and to study the relation between the pharmaceutical companies for various measures of profitability. The study period is ten years from 2007-08 to 2016-17. Based on the study it can be seen that pharmaceutical companies had a very good profitability in 2008, while the weakest profitability of all time in year 2015.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".