Bibliographic record
Abstract
“There is a great satisfaction in building good tools for other people to use.” Freeman John Dyson, Disturbing the Universe Programmable calculators in the late 1970s and personal desktop computers in the early 1980s put the brute force of iterative calculations for statistical data analysis within the reach of all epidemiologists, students, and established professionals alike. At the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia, Ray Simons was a scientific photographer already celebrated for his work on the pages of Time-Life, National Geographic, and other magazines. To achieve this photographic excellence, he had written programmable calculator software to adjust his camera lenses and allow him to capture nature and biologic phenomena with unsurpassed clarity. At the CDC, Ray met epidemiologists coping with Legionnaires’ disease, toxic shock syndrome, and the developing acquired immunodeficiency syndrome pandemic. Armed with his programmable pocket calculator and a self-acquired knack for statistics, Ray generously spent hours trying to solve the computational problems people brought to him. He was passionate about finding simple solutions for numerical problems that the CDC faced every day. In 1983, he received a Superior Performance Award from Dr. William Foege, who was the director of the CDC at the time, for his work in writing the computer programs used in epidemiologic data analyses at the center. Ray retired from the federal service in 1987 but continued to influence the development of epidemiologic software. He inspired many of us with his generosity and passion for developing simple software for use in the field by epidemiologists. He profoundly touched the lives of the 3 of us, his intellectual soul mates who shared with him the vision in the above Dyson quotation, which later took the form of public domain and open source software. He would write and rewrite lines of programming code like a poet editing a sonnet, constantly striving to make the algorithms tighter and faster to fit the memory and processing capacity of an available handheld calculator and to increase their esthetic value. Ray never earned a doctorate; rather, he focused the considerable heft of his intellect and ability on his creative work. Although not a card-carrying epidemiologist, he was a devoted developer and user of the tools of our trade. His brilliance went hand-in-hand with his kindness and pure passion for epidemiology and biostatistics. Always with self-effacing humility, he took great satisfaction in seeing others improve on the work he started, and he inspired us to do the same. His influence in epidemiologic computing can be traced not only to lines of code that are part of widely used epidemiologic software programs but also to the many improvements and bug fixes that his sharp eyes and statistical skills inspired. His work in transforming complex algorithms into elegant and concise programming code spanned the entire range, from exact confidence limits for proportions to 2 × 2 contingency tables to regression analyses and stochastic modeling of infectious disease epidemics. Like Dyson, Ray believed that science and religion provide 2 different windows into our world and our existence in it. He peered into his meaning in life through both windows, and this brought him the inner peace needed for his creativity and strength. To him, these windows brought nonconflicting views that guided him morally as a husband, father, and member of his community. Until a few weeks before his passing on May 15, 2012, from the consequences of a brain tumor, he was busy writing e-mails to us, perfecting programming code, and asking how our children were doing. His hundreds of e-mails to friends and family are a fascinating collection of essays, cartoons, photographs, evangelism, science, and statistics. Our professional community has many unsung heroes. In recognizing Ray Simons’ legacy, we also seek to pay tribute to the champions of our profession who preferred to avoid the limelight while giving us the tools of our trade.1 Conflict of interest: none declared.
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 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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".