Bibliographic record
Abstract
It’s a great honor and privilege for me to assume the role of the Editor-in-Chief of IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), which started in January 2024. I have been involved in the editorial services of TCSVT for over 23 years in various capacities. I attended my first TCSVT editorial board meeting at ISCAS 2000, and since then I served as an Associate Editor of TCSVT for four terms, working with Editor-in-Chiefs, Prof. Weiping Li, Prof. Thomas Sikora, Prof. Chang Wen Chen, Dr. Hamid Gharavi, and Prof. Dan Schonfeld. I also served as a Guest Editor of TCSVT three times and served as the Associate Editor-in-Chief of TCSVT under Editor-in-Chief Prof. Feng Wu from January 2020 to December 2021. Conducting services for TCSVT has been an important academic activity across my whole career. Therefore, I look forward to this exciting yet challenging opportunity to lead TCSVT to the next level.
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 | 0.007 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.118 | 0.118 |
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".