Distinguished Microwave Lectures: An Enriching Experience for MTT-S Members and Speakers [Women in Microwaves]
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 offers a Distinguished Lecturers Program, allowing Chapters to host distinguished lecturers who are excellent speakers and experts in their respective topical fields. Within the IEEE Microwave Theory and Technology Society (MTT-S), this program is renamed the Distinguished Microwave Lecturers (DMLs) Program. In the summer of 2022, the MTT-S announced the DML class for 2023–2025. We observed that this was the 10th all-male class since 2009. In fact, there have been only five female DMLs since the 2009 class, including the present two female DMLs. A major reason is the lack of nominations of female candidates. The same observation is valid in terms of geographical diversity. Therefore, this column elaborates on the nomination process and shares the experiences of female DMLs.
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 | 0.000 | 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