Bibliographic record
Abstract
Murray Speirs has made important and lasting contributions to ornithology and natural history in Ontario.He is the recipient of the OFO Distinguished Ornithologist Award for the year 2000.Born in 1909, Murray was fascinated by birds as a lad; at age six he identified his first Ruby-crowned Kinglet.In his teen years, he was one of the most active birdwatchers in Toronto and by age 15 he was keeping records of the species and numbers of birds he saw, a practice he kept up until he was 90.His interest in science took him through the Mathematics and Physics course at the University of Toronto but he soon turned his quantitative skills to Fluctuations in the Number of Birds in the Toronto Region, the subject of his Master's thesis in the Department of Zoology.For this study, he gathered together field notes and publications of many other observers along with his own, an approach that was to characterize many of his later projects.His doctoral studies with Dr. Charles Kendeigh, a well-known ecologist at the University of Illinois, were interrupted by a stint as meteorologist with the ReAF during World
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.206 | 0.095 |
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".