Bibliographic record
Abstract
ohn Sellers passed away at his home in Carleton Place, Ontario January 9, 2005 with his wife, Marilyn, at his side.John had suffered from a respiratory ailment for a number of years and had recently had a severe case of pneumonia that had him in hospital just before Christmas.A family service, with a few close friends in attendance, was held January 14 at St. James Anglican Church, followed by a celebration in the Parish Hall of John's life.In the words of the church group who catered the event, it was the largest assembly they had ever served.The words are an apt analogy for John's life and career.He was larger than life in many ways -a devoted family man, a caring and giving friend, a forester's forester, an avid dancer (square and round), an accomplished woodworker and turner, a devout member of the Anglican Church of Canada, an eager webmaster, a (sometimes frustrated) fisherman, an entrepreneur, a helping hand wherever and whenever it was needed.The list goes on, and John touched the lives of many, many people.After Grade 13 at North Toronto Collegiate, John entered the Faculty of Forestry, University of Toronto in the fall of 1957.He was an above-average student and graduated with a B.Sc.F. in 1961.Shortly afterwards, he married Marilyn Davidge whom he had met in their teen years through the Bedford
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.124 | 0.027 |
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".