Correctional Service Canada's “next generation” command and control systems architecture
Bibliographic record
Abstract
Correctional Service Canada (CSC) operates 57 Institutions equipped with a range of mission critical Security, Communications and Access Management systems. These include CCTV assessment, intrusion detection, radio communications and door control systems. User Interfaces range from colour graphic touch screens to knobs, push buttons etc. Operational and technical challenges include the following issues: 1) sub-system technology is vendor specific, 2) reliability is critical in a challenging environment, 3) system maintenance is expensive, 4) inconsistent "Look and Feel" resulting in usability issues, 5) costly to add new systems, multiple, legacy and proprietary protocols & connectivity approaches, legacy installations are cable intensive, 6) minimal operator or maintenance training crossover, 7) procurement requirements drive "silo" system implementation. The objective is to develop a "next generation" systems architecture that will: "abstract" the subsystem user management interfaces, ensuring all sub-systems can be managed using a simple, consistent graphical user interface, accessible using a web browser; model the data and behaviour of the edge devices, doors; cameras, sensors, etc. and normalizes it; allowing them to be managed by and provide notifications to standard software based applications; support inter-domain interoperability; use an industry standard communications protocol, likely with extensions, such as BACNet or SNMP, for edge device to application server connectivity; use TCP/IP over fibre as the preferred transport, network and physical technologies; integrate legacy sub-systems into the application server using mediation software; define the look and feel of the graphical icons that represent the edge devices and the physical environment in which they are placed, so that each domain is presented in a consistent manner. Developing and adopting this architecture will allow Correctional Service Canada to address the challenges of its unique environment and support the definition, procurement and deployment of subsystems more effectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.133 | 0.046 |
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".