Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IEEE/CIC International Conference on Communication in China (ICCC) is one of the flagship conferences in Asian-Pacific region held by IEEE Communication Society (ComSoc) and China Institute of Communication (CIC). IEEE/CIC ICCC 2018 was held in Beijing, China, on August 16–18, 2018. The key theme is Ubiquitous Network, Intelligence and Society, which broadly covers the theoretical and practical innovations in the area of communications. The technical program of IEEE/CIC ICCC 2018 features 6 world-class keynote speeches which are presented by Wei-hua Zhuang (Fellow of IEEE, Royal Society of Canada, Canadian Academy of Engineering, and Engineering Institute of Canada), Abbas Jamalipour (Fellow of IEEE, IEICE, and Institution of Engineers Australia), Tao Zhang, Ying-Chang Liang (IEEE Fellow), James Kimery, and Sumei Sun (IEEE Fellow). The invited speakers of IEEE/CIC ICCC 2018 included Yue Gao, Zhi Ding (IEEE Fellow), Tony Q.S. Quek (IEEE Fellow), Kwang-Cheng Chen (IEEE Fellow), Jian-wei Huang (IEEE Fellow), Zhu Han (IEEE Fellow), Klaus Moessner, Tommy Svensson and Qinyu Zhang.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it