An Advanced hygrothermal design tool "I-D hygIRC"
Bibliographic record
Abstract
1-D hygIRC is a user-friendly one-dimensional version of IRC's hygIRC, a state-of-the-art hygrothermal computer model. 1-D hygIRC has being made available for public release. The basic component modules comprising 1-D hygIRC are: the recently benchmarked hygIRC solver, a climate database containing 30 to 40 years of hourly weather data for 19 Canadian and 6 US cities, a material database containing the hygrothermal properties of 80 common construction as measured at IRC, a building envelope design tool integrated with the material properties database, and models to derive interior temperature and relative humidity conditions. 1-D hygIRC also provides the user with easy to use tools for output analysis. Optional provisions have also been made for the user to specify their own weather, interior conditions, or material property data, if they wish to investigate other parameters than those provided. The model simulates the hygrothermal response of each element to changing environmental conditions on either side of the envelope on an hourly basis. This produces information on the temperature and relative humidity distributions within the wall assembly and the changes over time. Time series plots of temperature, moisture contents, and other output parameters can be viewed for the wall layers or the entire wall where applicable. 1-D hygIRC also contains the freeze-thaw cycles and a moisture index developed for use with hygIRC. Users can animate the results to give a picture of the wall response over time. This program is targeted to engineers, architects, building scientists, contractors and other professionals. The framework of 1-D hygIRC was built to facilitate case studies allowing the user to readily conduct parametric studies, studies where several parameters are changed one at a time to gauge the sensitivity of the wall response. 1-D hygIRC can be downloading from IRC web site (http://www.nrc-cnrc.gc.ca/eng/projects/irc/hygirc.html).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.127 | 0.028 |
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".