IEEE Society Interaction, Industry Engagement, and Young Professionals Are the Future of the MTT-S [President’s Column]
Bibliographic record
Abstract
From my perspective in June 2023, the IEEE Microwave Theory and Technology Society (MTT-S) is a vibrant Society, with many activities ongoing related to our technical field. Several conferences have occurred with a significant impact on our members; those include the International Microwave and Antenna Symposium (IMAS), in Cairo, Egypt (Figure 1); the IEEE Wireless and Microwave Technology Conference, in Florida, USA; the IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, in Texas, USA; the IEEE MTT-S International Wireless Symposium, in Qingdao, China; and the IEEE Workshop on Signal and Power Integrity, in Aveiro, Portugal. For June, we have an entire month of events, including the brand-new Wireless Power Transfer and Exhibition, in San Diego, CA, USA; the IEEE RF Radio Frequency Integrated Circuits Symposium; our flagship conference, the IEEE MTT-S International Microwave Symposium; and the Automatic Radio Frequency Techniques Group Microwave Measurement Conference, all co-located in San Diego. At the end of the month, the International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization will be held in Winnipeg, MB, Canada. At all these events, we have a vibrant number of Young Professionals (YPs) events planned along with our industry colleagues, creating an excellent opportunity for academic, industry, and government interaction, impacting the future of microwaves and technology worldwide.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.075 | 0.058 |
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".