Bibliographic record
Abstract
It is our great pleasure to thank all of you for your participations to 2019 3rd International Conference on Power and Energy Engineering (ICPEE 2019) which was held during October 25-27, 2019, in Shandong University, Qingdao, China. ICPEE 2019 is organized by Shandong University, assisted by Xiamen University of Technology, via their South-South Collaborative and Sustainable Development Center and International Society for Environmental Information Sciences (ISEIS). ICPEE 2019 is dedicated to issues related to Power and Energy Engineering. It was a golden opportunity for students, researchers and engineers to interact with the experts and specialists to get their advices and consultations on technical matters, dissemination and marketing strategies. ICPEE 2019 is highlighted by several senior academic and professional speakers, including Prof. Gordon Huang from University of Regina, Canada, Prof. Edward McBean from University of Guelph, Canada, Prof. Yongping Li from Beijing Normal University, China, Prof. Zhijun Peng from University of Bedfordshire, UK, Prof. Christophe Guimbaud from National University of Orlean, France and Dr. Pengfei Xia from Center for Applied Geosciences, University of Tubingen, Germany who have attended the conference as keynote speakers. There were ten sub-sessions with various topics: Modeling of energy management systems, Energy and environmental Studies, Technologies of power and energy engineering, etc. These proceedings present a selection from papers submitted to the conference by universities, research institutes and industries. All papers were subjected to peer-review by conference committee members and international reviewers. This volume is presenting recent advances in the field of Environment and Renewable Energy and various related areas, such as High voltage transmission and insulation technology, Smart Grid Operations and Management, Mechatronics, Power system and performance assessment, Electrical engineering and automation, Electricity and energy, Electronic information engineering. We would also like to express our sincere gratitude to organizing committee and the volunteers who had dedicated their times and efforts in planning, promoting, organizing and helping the conference. Prof. Zhijun Peng University of Bedfordshire, UK 2019-11-18
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.004 |
| Insufficient payload (model declined to judge) | 0.484 | 0.346 |
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".