Innovative Development of Renewable Energy During The Crisis Period and Its Impact on the Environment
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 article examines the innovative trends in the renewable power generation, taking into account the impact of crises, as well as the impact of renewable energy on air pollution in the world (environmental change). Hierarchical agglomerative and iterative methods of cluster analysis, as well as econometric models were used to test the hypotheses. Carbon dioxide emissions and renewable power generation for 78 countries during 2000-2020 are taken into account as the database of the study. The results showed that there are groups of countries with sharp, high, moderate and low growth rates of renewable power generation. In addition, the results of econometric analysis indicate that the growth of renewable power generation does not always cause a decrease in carbon dioxide emissions. For a number of countries (Australia, Canada, Mexico, Poland) such connection is not essential at all. The results of the study can be useful in shaping and adapting environmental strategies around the world.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it