The Impacts Of COVID-19 Pandemic on Greenhouse Gas Emissions and Climate Change
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
The outbreak of COVID-19 in 2020 has brought enormous damage to human life and health and socioeconomic development. Yet, the influence of COVID-19 outbreak on the environment within the context of global warming has not been fully understood. Detailed and accurate explanation for the relationship between COVID-19 and economy, carbon emissions, and methane emissions remains a challenge. This study aims to highlight the significant impact of the COVID-19 pandemic on greenhouse gas emissions and climate change through a systematic literature review and comprehensive analysis of data from the U.S., China, Canada, and 27 European countries. To clarify the impact of COVID-19 on climate, the study outlines changes in carbon dioxide emissions by comparing data from pre-pandemic, during-pandemic, and post-pandemic (projected) scenarios. The correlation among carbon dioxide, temperature, GDP, and Population in countries is further examined with different levels of development using Pearson's Linear Correlation analysis and significance test. This study will potentially provide insights into future preparation and management of the impact of global emergency disaster emergencies.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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