Cooperation with Industry in Real-time Systems at CRIM
Bibliographic record
Abstract
Given the increasing pressures on the private sector to be competitive in the world market-place, governments, industry, and universities have come to understand the importance of encouraging technology development within the framework of technology transfer. The Computer (science) Research Institute of Montreal (CRIM) or in French, le Centre de recherche informatique de Montreal, was created in 1985 to address such needs by pooling resources from the public, private, and para-public sectors in the province of Qu'ebec to perform R&D activities in key areas of information technologies including real-time systems. In this article, we begin by presenting CRIM, its mission and activities, and then we describe the kinds of education and technology transfer which take place at CRIM with specific emphasis on two collaborative projects involving industrial partners, CRIM staff, university professors and their graduate students in the area of computerized control systems. 1 CRIM at a glance T...
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".