Wood-cement-steatite panels used in replacement of gypsum boards in residential and commercial buildings: contribution to the thermal mass
Bibliographic record
Abstract
This article reports the results of a study carried out to evaluate the influence of wood-cement-steatite partitions on the thermal performance of a small building. The interior walls of two identical 2.0 × 2.5 × 3.0 m experimental wooden frame huts (tiny houses, with one door and one window), designed and built following the National Building Code of Canada, were covered with standard gypsum boards in one case (GB hut) and a combination of gypsum boards and wood-cement-steatite panels in the other case (WCSP hut). The thermal behavior of both huts, located on the campus of Laval University, in Québec (QC), Canada was monitored over a testing period extending from mid-march to the first week of July 2019. Depending on the moment during that period (cold weather, mild weather) and the characteristics being evaluated, the temperature inside the huts was conditioned or not with an electric heater. The following parameters were recorded: outdoor temperature, the temperature inside the two huts, and, when applicable, their electricity consumption. In cold weather, the wood-cement-steatite panels contributed to reducing the electricity consumption by 5.2% over that of the reference GB hut. In mild weather, wood-cement-steatite panels were found to improve the comfort inside the test hut by leveling off the temperature variations, with reductions ranging from 0.3 °C to 3.8 °C. Both the differences in electricity consumption and indoor temperature variations were determined to be statistically significant, with p - values inferior to 0.005. The results generated in this part of the study further strengthen the potential of WCSP as a real alternative to gypsum boards for drywall partitioning in residential and commercial buildings. In addition to their many advantageous constructive properties, such as water resistance, flexural strength, screw withdrawal resistance, and fire resistance, the improvements they could yield in energy efficiency and thermal comfort make it a quite promising partitioning option.
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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 | 0.001 | 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".