Miles Copeland: Three Decades of Scientific Excellence and Industrial Relevance
Bibliographic record
Abstract
We know Miles Copeland well as an academic, having attended his graduate-level courses and then having the pleasure of working alongside him at Carleton University in Ottawa, Canada, delivering courses on selected topics in IC technology to graduate students. We know him better through a series of intensive collaborations in the industrial setting of Bell-Northern Research (BNR) and Northern Telecom (NT, later just Nortel) that began in the early 1970s. Miles, from the perspective of local industry, was not just seen an international leader in the field of analog/mixed-signal/RF IC design; rather, we were mentored by him personally as a technical expert. We also watched him mentor generations of graduate students as a professor, teacher, and advisor at Carleton. He and his research teams have consistently produced innovative results of the highest quality that have been extensively published and recognized by peers, his academic institution, and industry as an extraordinary body of work.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".