Editorial Introduction of New Editor-in-Chief (EIC) and Deputy EIC
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
After a brief review of the publishing statistics for the IEEE Embedded Systems Letters , the current Editor-in-Chief (EIC) introduces the new leadership team of Prof. Krithi Ramamritham as EIC and Catherine Gebotys as Deputy EIC. This leadership emerged after an extensive search for the EIC earlier this year. Prof. Ramamritham is an Endowed Chair Professor of Computer Science and Engineering at the Indian Institute of Technology, Bombay, and the author of almost 500 papers spanning many areas of embedded systems including real-time systems, distributed systems, databases, and sensor networks. Prof. Ramamritham is a researcher par excellence to lead the journal, and brings a wealth of experience in journal leadership from his tenure as EIC of the Real-Time Systems Journal and has been associated with many editorial boards. Dr. Catherine Gebotys is a Professor and a Professional Engineer with the Department of Electrical and Computer Engineering at the University of Waterloo, Waterloo, ON, Canada, and is the author of over 100 papers in the areas of electronic design automation, embedded systems security, and low-power design, Dr. Gebotys brings a wealth of research and practical experience built over two decades in the industry and academia.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it