Bibliographic record
Abstract
The 2023 International Conference on Chemical, Energy Science and Environmental Engineering (CESEE 2023) was held in Sanya, China during April 14-16, 2023. Considering travel restrictions, the conference was held in a hybrid format, including both on-site and cloud meetings. This was the first CESEE conference, intended to be repeated annually. This conference aimed to provide an attractive platform for academics, scientists, researchers, experts, entrepreneurs, and students to express and discuss their interests in chemical, energy and environmental engineering. The participants were from almost every part of the world, with various background such as academia, industry, and well-known entrepreneurs. More than 30 participants attended the conference online and offline, including China, Canada, Belgium, Argentina, Malaysia, Turkey, Uzbekistan and more. There were four renowned speakers who illustrated their latest research, to include Prof. Marc Rosen from Ontario Tech University, Canada; Prof. Jan Baeyens from the Beijing University of Chemical Technology, China and KU Leuven, Belgium; Prof. Nour Shafik El-Gendy from the Egyptian Petroleum Research Institute (EPRI), Egypt; and Prof. Ahmad Zuhairi Abdullah from University Sains Malaysia, Malaysia. The conference also had 2 technical sessions and 1 poster session. CESEE 2023 became an effective communication platform for all the participants who took the opportunity to share their research results and discuss potential scientific and engineering developments from their work. This contributed to the success of the conference. The conference proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. All papers in the proceedings have passed the vigorous review process involving reviewers by the international technical committee. The variety of research topics presented in the conference and novelty exhibited in the papers published in the proceedings demonstrated the impact of CESEE 2023. List of Committees are available in this 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".