A Tribute to Dr. Ronald Hardy for his Contribution to \nAquaculture Nutrition.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ronald William Hardy was born in 1947 in Vancouver, Canada. He comes from a very academically able Canadian/Scottish family. His grandparents came from Scotland and moved to Vancouver in 1909. In his father´s family there were doctors, nurses and also missionaries in Canada near Alaska. Ron´s father worked in agriculture communities around Seattle (an expert in poultry science), and used to take his 6 years old son salmon fishing, that was Ron´s first connection with salmon and trout. His mother came from a family of Scottish farmers, and then scientists; she was a Microbiologist and worked on tuberculosis. Ron took pre-medicine curriculum for 4 years, receiving his BS in Zoology in 1969 at the University of Washington. He took many jobs, including on farms and railroads, to pay for his college education. In 1970 he married Elizabeth the future mother of his daughters (Anna and Clare). Then in 1973, he obtained a M.S. in Animal Sciences/Nutrition at Washington State University; his thesis subject was “Studies on factors in rye which cause growth depression in chicks”. One day at the University Library he found the book of Dr. Halver on fish nutrition and, discovering the important gap in this area with respect to poultry, porcine and bovine nutrition, realized the huge potential of this new activity. Halver´s book was his second inspiration… It was at this time that he commenced his life‟s work on the nutrition of fish, graduating with a PhD in Fisheries at the University of Washington, Seattle (1978). Hardy‟s PhD dissertation subject was “Effects of dietary protein and pyridoxine levels on growth and disease resistance of chinook salmon”, having as mentors Dr. Halver (biochemistry and nutrition) and Dr. Brannon (salmon biology).
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it