Tracking Trends in Canadian Gastroenterology Research
Bibliographic record
Abstract
Metabolism and Diabetes (INMD).The institute supports research directed at enhancing health in relation to diet, digestion, excretion and metabolism; and includes research relevant to a wide range of conditions and problems associated with the digestive system, kidney and liver function, and hormones.PA: Over the past years, many gastroenterologists and scientists have, unsuccessfully, tried to create a CIHR Institute for Digestive Diseases.Presently, many of our research projects are under the umbrella of the CIHR -INMD and as a result, many gastroenterology researchers feel at a disadvantage compared with other specialties with their own institute.DF: There were a large number of groups who petitioned for their own institute and there are many ways to divide up responsibilities among institutes.My own sense is that the architects of the CIHR found the right balance between the number of institutes and the type of focus.I tend to place the institutes in three categories: disease and body part institutes (eg, the INMD, the Institute of Circulatory and Respiratory Health and the Institute of Cancer Research), vulnerable population institutes (eg, the Institute of Aboriginal People's Health and the Institute of Aging) and types of research institutes (eg, the Institute of Genetics and the Institute of Population and Public Health).This mix has brought together a diverse group of scientific directors to help shape the directions of the CIHR.It also means that many researchers will be interested in an affiliation with multiple institutes and the institutes must work together to develop initiatives.Funding for gastrointestinal (GI) and liver research at CIHR has grown at the same pace as the CIHR's grants and awards budget (1.9-fold) since fiscal year 2000/2001 (Figure 1).Approximately one-half of the liver research grants were for hepatitis-related projects.The funding channelled through each institute is a relatively small portion (approximately 1%) of the CIHR grants and awards budget and is intended for strategic initiatives.The INMD's initiatives are motivated by our strategic plan, which articulates our focus on obesity and strategic partnerships across our mandate.The INMD supports GI training through the Strategic Training Initiative in Health Research and University Industry programs.We support workshops like
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.031 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".