Feature Story: Western Canadian Innovation Offices – developing Industry Identified Research Initiatives program
Bibliographic record
Abstract
On July 29, 2015, Honourable Michelle Rempel, Minister of State for Western Economic Diversification announced $1.8 million in funding for a collaborative new project to support research and development in various sectors, starting with the energy sector. Initiated by Western Economic Diversification in January 2014, the University of Manitoba will lead the development and formalization of the Western Canadian Innovation Offices (WCIO), a consortium of universities, including the U of R, colleges, polytechnics and other research based organizations in western Canada. Their mandate will be to work collaboratively together and with industry to carry out research that addresses industry needs, builds a more entrepreneurial culture, commercializes technologies, and creates jobs and improves economic performance in Western Canada.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.004 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.061 | 0.013 |
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".