Furnace tests : the National Research Council of Canada is investigating a way to test the fire resistance of wall and floor assemblies that is more economical than doing full-scale tests
Bibliographic record
Abstract
In recent years, fire-rated floor and wall assemblies formed with new materials and construction methods have been used increasingly in residential buildings. To determine the fire resistance performance of these assemblies, full-scale tests are usually required. However, these tests are expensive and time consuming, and there is a need on the part of design engineers and architects, at least in the development of assemblies, to find an alternative solution. To satisfy this need, the National Research Council of Canada (NRC)has been developing a simpler and less expensive test method for these purposes. As part of these efforts, NRC has just completed the construction of an intermediate-scale furnace that can be used for testing loaded and unloaded wall and floor assemblies. However, to ensure that this furnace reflects full-scale test results, it must be characterized. Heat exposure in the furnaces is one of the critical parameters in determining the fire resistance performance of specimens. This article presents results of the heat exposure characterization tests carried out by NRC in both its full- and intermediate-scale fire resistance floor test furnaces.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".