Bibliographic record
Abstract
While existing structures present an excellent opportunity for energy savings, it has been established that thermal upgrades to masonry buildings by interior insulation significantly increase the risk of freeze-thaw deterioration of the bricks. Before implementing such retrofits, it is important to understand the risk of damage to the masonry envelope. The critical saturation approach has been proposed as a method for conducting a risk assessment of the freeze-thaw resistance of in-service brick masonry. In order to produce valuable insights, any hygrothermal simulation and analysis relies on the input of accurate material and hygric properties and the outputs must be compared to well established targets. Therefore, it is of interest to verify the reproducibility of the experimental measurements of such properties. Factors such as operator, equipment, and procedural differences can produce deviations in measurements obtained from different laboratories. The critical degree of saturation is the principal metric in this risk assessment framework and is determined by an experimental methodology called frost dilatometry. As the critical degree of saturation is used as the threshold for risk in this limit state design process, it is important to understand the precision of this measured value. Frost dilatometry measurements were conducted at two different laboratories to examine the reproducibility of the critical saturation measurements for 30 brick samples. Dilation measurements are determined with an uncertainty of 50 microstrain. The data analysis methods are examined as a source of discrepancies between lab measurements. Procedural challenges and differences, such as specimen dimensions and number of freeze-thaw cycles, are examined. The saturated moisture content is determined by vacuum saturation. While the results between the two laboratories are generally in agreement, it is a source of error in comparisons of the critical saturation between labs. Correcting for differences in saturated moisture content, it was found that the measurement of the critical degree of saturation are in good agreement. The critical degree of saturation differs by 1-3% when expressed as a ratio of water content to the dry weight of the material indicating the reliability of critical degree of saturation measurements. While differences between the laboratories were small, the uncertainty of the critical degree saturation for both laboratories was large.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".