Analyzing the mechanism between nuclear energy consumption and carbon emissions: Fresh insights from novel bootstrap rolling-window approach
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
This research utilizes a bootstrap rolling-window (BRW) causality test to explore the causal interrelationship between nuclear energy consumption (NUC) and carbon dioxide emissions (CO 2 ) in 6 developed countries from 1980 to 2020. When there are structural shifts in the full-sample time series, empirical research exploring causality between two-time series generates erroneous conclusions. On the other hand, the BRW method allows researchers to find potential time-varying causality between time series using sub-sample data. The outcomes of the BRW causality test disclosed the following results: (i) a unidirectional negative causality from NUC to CO 2 without feedback was found for Japan; (ii) a negative causality at sup-sample periods from NUC to CO 2 surfaced at the sub-sample period while a positive causality surfaced from NUC to CO 2 in sub-sample period for the United States of America (USA) and France; (iii) a negative feedback causality between NUC and CO 2 was found For Canada; (iv) a positive unidirectional causality surfaced from NUC to CO 2 was found for Germany, which implies that consumption of NUC worsens the environment in the sub-sampled period. The results may have policy consequences for the selected developed countries regarding NUC and CO 2 nexus.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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