Europe’s Energy Crisis; Winners of the Crisis with Market Data
Bibliographic record
Abstract
Prices of natural gas, coal, and electricity have risen to the highest level of the last ten years in the last quarter of 2021. It’s possible to express that energy prices in 2021 were much higher, compared to the crisis of 2020’s Covid-19 breakout’s historical descent in the first few months. There are a few factors to this rally. The epidemic caused structural fractions on a global scale. But in general, there is no doubt that crisis factors, which mainly concern Europe, are not limited (with) recovery process in the economy. With this notion, the main structure of this work’s subject aims to analyze the lead-up to the energy crisis that became apparent in 2021. Also, in the work, the energy crisis that’s been occurring will be analyzed thoroughly, with the help of its dynamics and causes. Within the scope of the study, the Hatemi-J (2012) asymmetric causality test was run using the weekly stock closing data of EU natural gas prices (EUGP), Gazprom (XGASPR), and Equinor (XEQUNR) for the period 05.11.2017–28.11.2021. As a result of the analysis, a causal relationship between the variables was determined. However, the work will positively contribute to the literature, being a guide to the current situations and overcoming the similar crisis that might occur in the future.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".