IMPACT OF CORONA VIRUS COVID-19 ON THE GLOBAL ECONOMY
Bibliographic record
Abstract
The present article dealt with the impact of COVID-19 outbreak on the world economy. The study has covered the outbreak of corona virus along with its impact on agriculture, energy sector, space science and overall economy. Coronavirus posing serious, challenging and troublesome effects on the economy is believed to create sudden economic recession which will burst the estimated budget of the world in the very first quarter. The global economic recession is expected to make a loss of trillion dollars of global income. Due to this pandemic spread over all the world wide webinars and conferences across technology along with sports and fashions are being postponed or being cancelled and it also led to shutdown of shops and companies except pharmaceuticals and groceries etc. which shows that there will be negative impact on the economies of the countries. It has made numerous impacts in agricultural sector affecting income and profit of farmers as well as distributors and consumers. Hence, there is a urgent need of government action and advanced research labs so that the world with all its major affected countries could turn the situation over and make the economic growth could reach little far towards the target.
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 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 | 0.002 |
| 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) | 0.001 | 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 teacher head, 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".