Bibliographic record
Abstract
In 1979, the first IEEE Milestone was dedicated in collaboration with the American Society for Civil Engineers and the American Society for Mechanical Engineers. Four years later, on the eve of the IEEE centenary celebrations, the IEEE Milestones program was officially launched with a mandate to draw the attention of both the public and the profession to significant events and accomplishments in electrical and computer engineering and related fields that occurred at least 25 years in the past. Although the Milestones program started slowly, it rapidly gained momentum. More than 20 Milestone proposals are now being submitted each year. As of September 2025, 276 Milestone plaques have been dedicated with many more approved and awaiting dedication. With the 300th Milestone dedication looming and 50th anniversary of the first Milestone dedication just a few years away, the IEEE History Committee has initiated a review of the Milestones program with an aim to refining its procedures and processes to reflect current approaches to public history and address operational challenges. Here, we reflect on the history, accomplishments, and challenges of the Milestones program to date and propose ways in which the program can be enhanced to ensure its relevance and efficacy in the decades to come.
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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 | 0.034 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.021 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".