Commercialization of university research in Canada: An NRC/IRAP perspective
Bibliographic record
Abstract
The National Research Council's Industrial Research Assistance Program (NRC-IRAP) is one of several Government of Canada programs that seek to bridge the gap between invention and successful commercialization. In order to successfully bring an invention to market, several key elements must co-exist: 1) the invention itself, 2) a viable and addressable market to consume the invention, 3) sufficient funds to convert the invention into a product, 4) a viable business model with acceptable gross margins to generate sufficient profits from product sales and 5) the people with the passion to transition the invention into a product. NRC-IRAP's considerable experience in supporting small technology companies has enabled it to more effectively identify and recognize the issues that these new firms must address before they can succeed in the market. This, in turn, has allowed NRC-IRAP to develop innovative support pillars that help new firms succeed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".