Bibliographic record
Abstract
Supported by I-Shou University and Xi’an University of Technology, the 7th International Conference on Water Resource and Environment (WRE2021) was successfully held online via Microsoft Teams Meeting from November 1-4, 2021. About 150 participants from 31 countries and areas, including United Kingdom, Uruguay, Romania, China, Russia, Germany, Thailand, Japan, India, Malaysia, United States, South Africa, Portugal, Canada, Indonesia, Norway, Poland, Vietnam, Philippines, Greece, Slovakia, Uzbekistan, Italy, etc., have joined the conference. The technical program of WRE2021 comprised 4 keynote speeches, 24 invited speeches, 72 oral presentations and 21 poster presentations. Two welcome speeches were delivered separately by the Conference General Chair Prof. Jiwei Zhu from Xi’an University of Technology (lasted for 10 minutes) and the Technical Program Committee Chair Prof. Chih-Huang Weng from I-Shou University (lasted for 10 minutes). Four keynote speeches were delivered by Emeritus Prof. S. A. Abbasi from Pondicherry University (India), Prof. Dominic C. Y. Foo from University of Nottingham Malaysia (Malaysia), Prof. Teik-Thye Lim from Nanyang Technological University (Singapore) and Assoc. Prof. Rengui Jiang from Xi’an University of Technology (China), each keynote speech was lasted for 45 minutes including questions and answers. List of WRE2021 Scientific Committee Members are 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 | 0.001 | 0.008 |
| 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 | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.613 | 0.421 |
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".