Bibliographic record
Abstract
Human being is currently dealing with a pandemic known as COVID-19, a highly contagious pandemic with unprecedented health crisis worldwide. This crisis has seriously affected communications, jobs, manufactures, commerce, consumption and human life. Affected international transport sector resulted in the disruptions of shipping, along with the new policies toward economy, travel restriction and border shutdowns, led to a dramatic increase in the trade costs. In the first quarter of 2020, this had a significant impact on global trade. This paper is utilizing an analytical methodology that aggregates, collects and categorizes relevant domestic and international reports on the COVID-19 pandemic, government policies, the degree of uncertainty of economic policies and its effect on trade costs. In the present study, we first brightly described the travel restriction measures taken by WTO members, secondly, the impact of the COVID-19 pandemic on trade costs, government pandemic response policies in the early stages of the COVID-19 pandemic were discussed ultimately we analyzed the effect of the significant increased trade costs on the global trade and its relevant roots. In this paper we used an integrated analysis method to collect and classify domestic and international reports on the COVID-19 pandemic through reports of WTO and the member countries.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".