Bibliographic record
Abstract
Xianghui Xie, JiangNan Institute of Computing Technology, China Xiaowu Chen, Beihang University, China Xiaoshe Dong, Xian Jiaotong University, China Wei Chen, Microsoft Research Asia, China Zhichen Xu, Yahoo! Inc., USA Yafei Dai, Peking University, China Yuan Xue, Vanderbilt University, USA Beixing Deng, Tsinghua University, China Yu Chen, Microsoft Research Asia, China Mingzhong Xiao, Peking University, China Wei Zou, Peking University, China Wanlei Zhou, Deakin University, Australia Yiming Hu, University of Cincinnati, USA Xiaofei Liao, Huazhong University of Sci. & Tech., China Lidong Zhou, Microsoft Research, USA Shuigeng Zhou, Fudan University, China Hongli Zhang, Harbin Institute of Technologym, China Yingfei Dong, University of Hawaii, USA Shoubing Dong, Huanan University of Sci. & Tech., China Hongling Yu, Tsinghua University, China Qianni Deng, Shanghai Jiaotong University, China Yingchun Yang, Zhejiang University, China Mark Baker, University of Portsmouth, UK Jinjun Chen, Swinburne University of Technology, Australia Ewa Deelman, University of Southern California, USA Schahram Dustdar, Vienna University of Technology, Austria Yushun Fan, Tsinghua University, China Geoffrey Fox, Indiana University, USA Wolfgang Gentzsch, D-Grid Germany, and RENCI, USA Karthik Gomadam, University of Georgia, USA Andrzej Goscinski, Deakin University, Australia Yanbo Han, CAS, China Ken Hawick, Massey University, New Zealand Jane Hunter, The University of Queensland, Australia Hai Jin, Huazhong University of Science and Technology, China Minglu Li, Shanghai Jiaotong University, China Omer F. Rana, University of Cardiff, UK Paul Roe, Queensland University of Technology, Australia Feiyue Wang, The University of Arizona, USA Andrew Wendelborn, University of Adelaide, Australia Mengchu, Zhou, The New Jersey Institute of Technology, NJIT, USA Albert Zomaya, The University of Sydney, Australia Subhash Bhalla, The University of Aizu, Japan Jiannong Cao, Hong Kong Polytechnic University, China Daoxu Chen, Nanjing University, China Pao-Ann Hsiung, Chung Cheng University, Taiwan Lijun Chen, Nanjing University, China Javier Garcia Villalba, Complutense University of Madrid, Spain Ching-Hsien Hsu, Chung Hua University, Taiwan Baocai Yin, Beijing Polytechnic University, China Antonio Puliafito, University of Messina, Italy Bin Xiao, Hong Kong Polytechnic University, China Incheon Paik, The University of Aizu, Japan Mieso Denko, University of Guelph, Canada
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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".