Special session 9B: New topic test facilities and infrastructure in Canada
Bibliographic record
Abstract
Over the last five years extensive test infrastructure has been deployed at Canadian Universities, funded by the Canada Foundation for Innovation (CFI) and managed jointly by CMC Microsystems, located at Kingston, Ontario and Principal Investigators at each of four sites. These test facilities are a part of the National Design Network (NDN) in Canada which has been developed over the last 25 years to serve researchers in the design, fabrication and test of microsystems prototypes. This presentation will outline the capabilities of the laboratories and the accessibility of the equipment through local and remote access. The four specialized laboratories enable the testing of Radio Frequency, Photonics, Mixed-Signal and High Speed Digital systems. About 200 researchers at 23 Canadian Universities participate in this `Testing Collaboratory' and they are connected using a wide area, fiber optic network provide by CANARIE. Hands-on assistance, training and specialist consultation is required for the operation of such sophisticated equipment and this is provided by CMC personnel on-site at each location. Activities include assistance in equipment configuration, sample or DUT management, provision of documentation, configuring of the communications links, development of tools for automation of test and data collection, and protection of Intellectual Property. Finally, a selection of the research that has been enabled by the wide availability of this infrastructure will be presented, including work on optical telecommunications systems, security threats to cryptographic systems, new signal processing techniques and RF MEMS devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".