Bibliographic record
Abstract
Abiomedical sciences professor was awarded the first Canada Research Chair (CRC) at the Ontario Veterinary College in November. Dr. Jonathon LaMarre will hold a junior chair in Comparative Biomedical Sciences for the next 5 years. The Canada Research Chairs Program, launched by the federal government in 2000, is designed to help Canadian universities become world-class research centers by providing them with new funds to recruit and retain outstanding faculty. Dr. LaMarre is an internationally recognized scientist whose research focuses on the regulation of gene expression in multiple species and tissues. He is currently studying the regulation of genes responsible for cell differentiation, growth, and angiogenesis, with the hope that this work will eventually translate into improved diagnosis and treatment of disease. “The idea is to look at very basic concepts about genes and how the genes are regulated, and ultimately to apply these concepts to animal and human disease,” he says. “Understanding the processes behind the regulation of gene expression is particularly important in the context of human and animal health where disturbances in normal control mechanisms contribute to the pathogenesis of many diseases.” Dr. LaMarre's research is comparative in every sense; he examines gene expression in multiple species models, including human, rat, murine, and bovine, and in different types of tissue within single species. He also compares gene regulation in normal and malignant cells. He is currently studying liver tissue and the regulation of hepatic lipoprotein receptor-related protein (LRP) synthesis. Lipoprotein receptor-related protein is a receptor implicated in atherosclerosis, tumor growth, and several other conditions, including Alzheimer's and cirrhosis. Dr. LaMarre hopes the Canada Research Chair will help him to recruit more talented young scientists to his laboratory. He currently supervises 2 PhD students, a postdoctoral fellow, and a technician. “One of the reasons I'm excited about this (Canada Research Chair) is it gives me the opportunity to train people who will become the next generation of investigators,” he says. Dr. LaMarre earned his DVM and PhD degrees at Guelph and has been a faculty member at OVC since 1993. His laboratory has received operating grants from the Canadian Institute of Health Research, formerly known as the Medical Research Council (MRC), since 1994. He also received funding from the MRC for both his PhD in Pathobiology and for the postdoctoral position he held at the University of Virginia Medical School. (by Natasha Marko, Public Relations Officer, Ontario Veterinary College, Guelph, Ontario)
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.160 | 0.049 |
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".