Bibliographic record
Abstract
COVID-19 has put a severe dent on the global economy and Indian Economy. International Monetary Fund has projected 1.9 percent for India. However, we believe that due to extended lockdown, the output in the first quarter is almost wiped out. The situation may improve in the second quarter onwards. Nevertheless, due to demand and supply constraints, input constraints and disruption in the supply chain, except agriculture, no other sector would be able to achieve full capacity of production in 2020-21. The signals from power consumption, GST collection, contraction in the core sectors hint towards a slump in the total output production in 2020-21. We derive the quarterly GVA for 2020-21 by using certain assumptions on the capacity utilisation in different sectors and using the quarterly data of 2019-20. We provide quarterly estimates of Gross Value Addition for 2020-21 under two scenarios. We have also estimated the fourth quarter output for 2019-20 under certain assumptions. We estimate
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".