SATI/CITAC technical evaluations - proving the quality and performance of new products
Bibliographic record
Abstract
CITAC and SATI, two independent organizations specializing in the technical evaluation and certification of urban infrastructure products, have signed a letter of agreement of cooperation that will facilitate and accelerate the acceptance and use of new products and technologies by Canada's urban infrastructure sector. Prior to signing the agreement, the Canadian Infrastructure Technology Assessment Centre (CITAC), part of the National Research Council's Canadian Construction Materials Centre, offered a technical evaluation service for new urban infrastructure products to facilitate their acceptance on national and international markets. The Service d'avis technique en infrastructures (SATI), formed by the partnership of the Centre for Expertise and Research on Infrastructure in Urban Areas (CERIU) and the Bureau de normalisation du Québec (BNQ), also offered evaluation and certification services for new products and technologies in Quebec with a view to making them available to Canadian and international markets. The cooperation agreement with CITAC is a step towards this objective. The agreement, signed in November 2002, allows the two organizations to offer a joint technical evaluation service to their respective clients. This involves developing a joint evaluation protocol for determining the suitability of a technology for its intended use. The protocol will include both testing methodologies and performance criteria for the new product of technology. Both CITAC and SATI will review the test results and compare them with the performance criteria to see if the technology meets the requirements. If the technology is deemed satisfactory, they will issue a single final joint evaluation report, which will be available through each organization's publication service.
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) | 0.000 | 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".