Research and Service: Celebrating a Role Model in the Radio Science Community In Honor of Gary S. Brown
Bibliographic record
Abstract
The author had the great privilege to develop a long-term professional relationship and friendship with Prof. Gary Brown and his wife, Kathy, during the course of a career that culminated in leading the US National Committee for the International Union of Radio Science (USNC-URSI). Over time this relationship included the author's wife and family, who also came to enjoy a friendship with the Brown family, meeting occasionally in Blacksburg, VA, as well as in various cities for various conferences and meetings. These meetings include the National Radio Science Meetings (NRSMs) in Boulder, CO, the summer meetings held jointly with the Institute of Electrical and Electronics Engineers (IEEE) Antennas and Propagation Society (AP-S), and the occasional North American Radio Science Meetings (NARSMs) when held with our Canadian National Committee for URSI (CNC-URSI) partners in several Canadian cities.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.015 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".