The effect of different mix proportions on the hygrothermal performance of hempcrete in the Canadian context
Bibliographic record
Abstract
Hempcrete is a light composite bio-based envelope plus insulation material with lime as binding agent and hemp as a renewable raw material from agriculture. The main qualities of hempcrete are hygrothermal behavior and low environmental impact. There is currently lack of clear cross-industry standards for hempcrete; however, extensive research, laboratory experiments and literature reviews are ongoing. The primary aim of this study was to understand the impact of different mixes on the performance of hempcrete and to establish hygrothermal behavior of a hempcrete wall in the Canadian context (by measuring dry density and some other hygroscopic parameters for 3 different mixes) as well as to define the required minimum thickness for a code compliant wall (as per OBC requirements) based on the most reliable reference R values. Based on the material values acquired from the tests and references, simulations for 2 types of wall assemblies and series of sensitivity analysis were carried out in WUFI software. Finally, further research on hygrothermal performance of hempcrete wall (using Canada grown hemp) was recommended to carry out by measuring thermal conductivity in various mean temperatures.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".