Cost Effective Basement Wall Drainage Alternatives Employing Exterior Insulation Basement Systems (EIBS)
Bibliographic record
Abstract
This paper compares the physical and economic (life cycle) performance of insulation materials placed on the exterior, above and below-grade portions of residential basements, in lieu of non-insulating drainage membranes and drainage layers, combined with internal insulation. The findings are premised on research, field studies and analysis associated with the Performance Guidelines for Basement Systems and Materials Project undertaken by the Institute for Research and Construction, National Research Council Canada. The thermal and drainage performance of several insulation materials installed on the exterior, basement portions of a test house located on the NRCC campus in Ottawa were monitored for a period spanning two heating seasons. In addition to assessing the effective, insitu thermal resistance of the insulation materials over the study period, the results for drainage effectiveness were also compared with conventional drainage layer and membrane materials commonly used in residential basement construction. An economic analysis of the exterior basement insulation system (EIBS) applications was also performed to compare their cost effectiveness with interior insulation applications relying on drainage membranes for exterior moisture protection. A comparison of critical considerations pertaining to exterior and interior basement insulation strategies is also presented, along with relevant conclusions based on the testing, energy modelling and economic assessment of EIBS. Ted Kesik is a professor of building science at Ryerson Polytechnic University, and currently Visiting Associate Professor in the Faculty of Architecture, Landscape and Design at the University of Toronto. Mr. Mike Swinton is a senior research officer at the Institute fo...
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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".