Tony F. W. Embleton in the Acoustics Section, Physics Division, of the National Research Council of Canada (NRCC)
Bibliographic record
Abstract
Tony completed his PhD in three years at Imperial College (London) studying under Dr. R.W.B. Stephens. He then joined George Thiessen and Edgar Shaw at NRCC to form the core of what became arguably the most influential and productive research group in acoustics in Canada from the 1960s to the 1980s. An important activity was service to industry, a role Tony embraced by collaborating with industry associations, participating in committees and directing his research activities. Working with George Thiessen, he succeeded in reducing the noise of couch rolls, a major source of noise in paper making, by randomizing the pattern of holes through which air was sucked to dry the paper. Other successful noise control projects included staggered stator blades for gas turbine engines and mufflers for rock drills. Tony made seminal contributions to outdoor sound propagation and refined condenser microphone calibration. In addition to his research and outreach, he found time for professional service to the ASA and CAA, including serving as founding editor of what is now Canadian Acoustics, and to develop standards and mentor younger scientists, He is remembered for his cheerfulness and willingness to provide advice and engage in conversation on any and all topics.
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.
How this classification was reachedexpand
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 | 0.005 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".