Wind power for the world: international reviews and developments
Bibliographic record
Abstract
Introduction, Preben MaegaardAccelerated Global Expansion of the Renewable Energy Sector: the Example of Wind Energy, Preben MaegaardWind Power Development in the European Union, Wolfgang PalzWind Energy to the rescue of mankind from the menace of the Fossil Fuel burning hazards, Anil KaneBlack or Green Wind Power, Frede HvelplundWind Energy Development in China, He DexinNon-grid-connected Wind Power and Offshore "Three Georges of Wind Power" in China, Gu WeidongWind Power in Japan: Past, Present, and Future Prospect, Izumi UshiyamaWind Power Development in India, Jami HossainChallenges and Opportunities for Energy Paradigm Shifting in Ontario, Canada, Jose EtcheverryWind Power in Cuba's Energy Revolution, Conrado Moreno FigueredoWind Power in Argentina, Erico SpinadelThe Emergence of Wind Power in Brazil, Everaldo FeitosaWind Energy in Chile, Arturo KunstmannWind Power in Austria, Wolfgang HeinThe History of Wind Power in France, Jean-Louis BalHistory, State-of-the Art and Future of Wind Energy in France, Marc JedliczkaThe German Law on Renewable Energies and the Development of Wind Power, Hans-Josef FellThe Beginning of a New Era in Wind Power Generation, John ChadjivassiliadisPolish Wind Power - Wind of Change?, Krzysztof PrasałekThe Development of the Wind Power Industry in Russia, Victor V. ElistratovWind Power Sector Development in the Russian Federation and Other Countries of the Commonwealth of the Independent States (CIS), Alina ProkopenkoWind Energy in Spain, Josep PuigThe Sleeping Giant. Sweden's Wind Energy Utilisation - a Short Overview, Arne JaegerUkraine: "Licensed" Way To Develop Wind Industry, Andrei Konechenkov and Galyna ShmidtEmerging Wind Energy Sector in Turkey, Tanay Sidki UyarWind Over Egypt, Dr. Galal OsmanMorocco: The Emergence of a Wind Power Country, Khalid BenhamouTowards Public Ownership and Popular Acceptance of
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.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".