Bibliographic record
Abstract
The research and application of efficient clean energy is the most important energy saving and emission reduction measure in China at the present stage, and the technological progress of clean energy power generation has also attracted the attention of experts and scholars all over the world. Therefore, the 2022 7th International Conference on Clean Energy and Power Generation Technology (CEPGT 2022) was successfully held during December 9th-11th, 2022 in Zhenjiang, China (virtual form), providing a shared platform for the international academic and engineering community. The International Conference on Clean Energy and Power Generation Technology is an international academic conference. Everyone interested in the fields related to Clean Energy and Power Generation Technology were welcomed to join the online conference and give comments and raise questions to the speeches and presentations. The online conference consisted of Keynote Speeches, Oral Presentations, and Academic Investigation, attracting about 50 individuals from all over the world. We have invited six sophisticated professors from different countries and regions to perform keynote speeches. Among them, Prof. Marc A. Rosen from Ontario Tech University, Canada delivered a wonderful keynote speech on Hydrogen Energy Systems: A Pathway to Sustainable Energy and Sustainable Development. Through hydrogen energy systems, the energy carrier hydrogen is a key facilitator of sustainable energy and can contribute significantly to attaining sustainability and sustainable development. As easily accessible fossil fuel supplies become increasingly scarce and environmental concerns escalate, hydrogen energy is likely to become increasingly important. With the world’s energy sources becoming less fossil fuel-based, hydrogen and electricity are expected to be the two dominant energy carriers for the provision of end-use services in a hydrogen economy. In this presentation, the role of hydrogen as an energy carrier and facilitator of sustainable energy was described and illustrated, and hydrogen energy systems that can contribute to a sustainable world were reviewed and discussed. All keynote speakers made brilliant speeches and shared unique professional experience and insights, triggering heated discussion in the conference. CEPGT 2022 received a great many submissions in the areas related to clean energy and power generation technology. Each submission was reviewed by at least two expert reviewers and the committee picked out some excellent papers that are included in the proceedings, covering but not limited to the following topics: Hydrogen and Fuel Cell, Green Energy Technology, Renewable Energy, Hydroelectric Power Generation, etc. On behalf of the Conference Organizing Committee, we would like to thank the Technical Program Committee members and external reviewers for their hard work in reviewing and selecting papers. And we would like to acknowledge all of those who supported CEPGT 2022. Particularly, our special thanks go to the editors and other members Journal of Physics: Conference Series. We deeply appreciate their efforts in making the conference successful. The Committee of CEPGT 2022 List of Committee member is available in the pdf.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.542 | 0.383 |
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".