Visionary Veterinarian: The Remarkable Exploits of Dr. Duncan McNab McEachran
Bibliographic record
Abstract
Few Canadian historical figures achieve the same notoriety as their American counterparts. Such is true of the 19th century Scottish-Canadian veterinarian, Dr. Duncan McNab McEachran. One of the most important pathogenic bacteria genera, Salmonella, was named for his now- immortalized American colleague, Dr. Daniel L. Salmon. Until now, McEachran had neither aggregated documentation of his work nor pathogens that share his name. In the classic style of many veterinary pathologists, Green relentlessly documents and describes McEachran’s life in this meticulously referenced book. One gets the impression that his diagnostic skills were suitably employed to research and uncover this story. There is ample use of photographs and images, which greatly complement the text. This book has broad appeal to anyone interested in veterinary medicine or Canadian history. The important role McEachran played in the history of veterinary medicine cannot be overstated. As Canada’s first Chief Veterinarian, he pioneered a world-renowned regulatory veterinary medicine system, initiated Canada’s livestock importation and quarantine structure, and excluded important foreign animal diseases. He established a veterinary school, ran a successful private practice, and worked with notable colleagues including William Osler, together identifying the dog lungworm (Oslerus osleri). In addition to veterinary medicine, McEachran bred horses and ranched cattle. As a businessperson and manager, the stories of McEachran’s involvement with some early western Canadian ranches offer a unique perspective. This book goes beyond a biography by painting a vivid historical picture of early Canada through the lens of veterinary medicine and suggests that perhaps there are many such amazing characters in Canadian history whose exploits remain undocumented. Given the breadth of McEachran’s fascinating activities, one wonders how he fit it all in! Surely this feisty Scotsman was no slouch and maybe someday soon, an important pathogen will bear his name.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".