Tony Embleton—Distinguished researcher, successful manager, consummate acoustician
Bibliographic record
Abstract
Tony F. W. Embleton was a distinguished researcher in acoustics. His early career focused on practical noise control projects and experimental non-linear acoustics. Later, Tony made important contributions to the understanding of sound propagation outdoors. Tony spent much of his career at the National Research Council of Canada (NRCC). His professional homes were the ASA and the CAA. Tony received numerous awards from the ASA for his work, including the R. Bruce Lindsay Award in 1964, the ASA Silver Medal in Noise in 1986, and the ASA Gold Medal in 2002 “For fundamental contributions to understanding outdoor sound propagation and noise control and for leadership in the Society.” Tony recognized the value of professional organizations and served the ASA as Vice-President (1977–78) and President (1980–81). He also understood the importance of practical applications in acoustics serving as ASA Standards Director (1993–97), navigating the organization through a tough period, and growing the program toward a solid future. Most importantly, Tony was known for his kind and generous spirit, and his outreach and inspiration to newer colleagues. Many of us are the grateful beneficiaries of his gentle enthusiasm.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.017 |
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".