Could Shale Gas Become a Reliable Energy Source for Europe and Romania?
Bibliographic record
Abstract
While shale gas and oil is a success story in USA and Canada where production has considerably increased in the last five years the situation is quite different in Europe where exploration and production activities are quite low and prospects are not encouraging. Even in the Eastern Europe the first results of exploration are disappointing for the American companies, which have the technical expertise for exploring and extraction shale gas. Due to global warming there is now at the world scale a fierce confrontation between environmentalists and lobbyists of producing companies regarding the negative effects of hydraulic fracturing. Shale gas development in Europe depends more on the coal substitution by gas and on the use of CCS technologies. The collapse of crude oil prices may delay many projects in the field of shale gas and oil, especially in Europe. The prospects of oil gas in Romania are linked to the energy security concept, whose implementation requires diversification of energy supply on some levels. The development of shale gas in order to diversify the energy supply cannot compensate the groundwater pollution and other negative effects, like earthquake. The temporary withdrawal of Chevron from Romania will have some positive effects, allowing to our country a necessary time-out to better substantiate public policies in the field and to producing companies some time required for carrying out new technologies, less polluting and harmful.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".