Professor Ralph Sturgeon, a researcher with an extensive and very significant scientific and administrative career kindly gave an interview to BrJAC
Bibliographic record
Abstract
Ralph Sturgeon received his Ph.D. in analytical chemistry in 1977 and has been with the National Research Council Canada since that time. His interests lie in inorganic analytical chemistry, comprising trace element analysis, vapor generation, organometallic speciation and production of Certified Reference Materials with a focus on atomic and mass spectrometry measurement techniques. He has published some 350 peer reviewed articles, a dozen book chapters and edited two books. He served as Editor for Spectrochimica Acta Reviews for 16 years, is a member of the advisory board of a number of international analytical chemistry journals and represented Canada’s interests at the International Bureau of Weights and Measures where he participated in the working groups for both Inorganic Analysis as well as the Joint Committee on Traceability in Laboratory Medicine for 14 years. His contributions to the analytical sciences have been recognized through a number of awards and distinctions, including Fellowship in the Chemical Institute of Canada (1990) and the Royal Society of Chemistry (UK, 2012), the Barringer and Herzberg awards of the Spectroscopy Society of Canada, the McBryde Medal from the Chemical Institute of Canada, the Ioannes Marcus Marci award of the Czech Spectroscopic Society, the Maxxam Award of the Chemical Institute of Canada and the Lester W. Strock medal from the Society of Applied Spectroscopy (USA). Most recently, he shared an Outstanding Achievement Award from the NRC (2022) in recognition of work in mass spectrometry. He holds three patents relating to sample introduction for atomic spectroscopy. How was your childhood? I enjoyed what I would say was a perfectly normal middle class childhood, but likely quite different from today’s generation, as mom was always home and only dad went to work. My two brothers and I were thus well looked after but never spoiled, although our parents were always a bit excessive when it came to Christmas celebrations. On the negative side, dad was always seeking a more challenging job and consequently the family moved across Canada at approximately 4 year intervals which, until I entered high school, tended to interrupt development of long-term friendships. I have a sharp memory of my father taking home study correspondence courses in the evenings to broaden his ability to advance in digital electronics. This instilled a sense of importance of education in me and my brothers such that we always knew we were destined for postgraduate degrees. I know that dad was very proud of all of us and our achievements.
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".