Mediating role of energy uncertainty for environmental management in electricity generation: The evidence from Pakistan
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Bibliographic record
Abstract
• The study examines the relationship between CO2 intensity, aggregated and disaggregated fossil fuels, clean and nuclear energy, and as a mediating variable, energy uncertainty for Pakistan. • We employ the ARDL Bound Testing method and wavelet coherence analysis for the empirical estimations. • The overall results suggest that under the mediating effect of energy uncertainty, renewables and nuclear energy in electricity generation have a negative association with CO2 intensity whereas fossil fuels in generating electricity positively influence CO2 intensity. • The rise in energy uncertainty leads to a fall in CO2 intensity in aggregated and disaggregated analysis as well. • Wavelet coherence analysis shows that CO2 intensity and energy uncertainty depend on each other dynamically for almost the whole employed period. This groundbreaking study examines the relationship between CO2 intensity, aggregated and disaggregated fossil fuels, clean and nuclear energy, and, as a mediating variable, energy uncertainty for Pakistan during 2019M01 and 2022M10 with monthly data. To this end, the ARDL Bound Testing method is used to identify the long-run relationship of the studied factors. The empirical results suggest that under the mediating effect of energy uncertainty, renewables and nuclear energy in electricity generation have a negative association with CO2 intensity. In contrast, fossil fuels in generating electricity influence positively CO2 intensity in the aggregated analysis. Moreover, the disaggregated results under the mediating role of energy uncertainty reveal that only hydro energy reduces CO2 intensity as renewables, bioenergy, wind, and solar energy do not impact CO2 intensity. Both coal and gas energies cause a rise in CO2 intensity. Regarding nuclear energy, it also has a negative relation with CO2 intensity. The increase in energy uncertainty leads to a fall in CO2 intensity in aggregated and disaggregated analyses as well. Wavelet coherence analysis shows that CO2 intensity and energy uncertainty depend on each other dynamically for almost the whole employed period.
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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 | 0.000 | 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 it