Bonny Specker - Professor Emerita, Health and Nutritional Sciences – SDSU
Bibliographic record
Abstract
Dr. Bonny Specker is Professor and Chair Emerita at South Dakota State University. She received her Ph.D. in Epidemiology from the University of Cincinnati and spent fifteen years on the faculty at Cincinnati Children’s Hospital Medical Center. In 1997, she moved to South Dakota as the E.A. Martin Endowed Chair in Human Nutrition. She has published extensively in bone, calcium, and vitamin D metabolism and in maternal and child health epidemiology. Since 2020 she has monitored the COVID-19 situation in South Dakota, posted regular blogs, and produced videos with the City of Brookings to educate the general public on basic epidemiological principles. Upon retiring in 2021, she has written a historical fiction titled “Spot On: The 1846 Faroe Islands Measles Outbreak,” inspired by the non-fictional investigation of the Danish physician and epidemiologist Peter Panum, and is currently writing her second historical fiction on the 1876-1877 Lake Winnipeg smallpox outbreak.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.085 | 0.024 |
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".