Bibliometric Assessment of Research Funded by Genome Canada, 1996-2007
Bibliographic record
Abstract
Genome Canada was established in April 2000 by the federal government to provide Canada with the capacity to undertake large-scale projects that would secure its position as a world leader in genomics in areas of strategic importance to Canadians (e.g., agriculture, environment, fisheries and health). Being a publicly funded corporation, Genome Canada is accountable for the value it creates through the funding of research and is therefore committed to the highest standards of good governance and responsible management It is in this context that Genome Canada is undergoing a second formative evaluation. As part of this exercise, Science-Metrix was mandated to provide performance measurements of the large-scale research projects supported by Genome Canada under its third objective, that is, to support the most promising genomics projects to be performed by outstanding researchers that could not have been funded through existing mechanisms given their scope and scale.
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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 | 0.011 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.143 | 0.374 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".