A Benefit-Cost Analysis of Impact-Resistant Asphalt Shingle Roofing--Overview
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Institute for Catastrophic Loss Reduction creates and disseminates disaster resilience knowledge for Canada. Among the catastrophes ICLR addresses are hailstorms, one of Canada’s most serious natural hazards. Hail costs $400 million annually. A June 2020 hailstorm at the edge of Calgary damaged 77,000 homes and cost $1.4 billion. Much of that money paid for roof repairs. A direct hit on Calgary could be 5 to 10 times worse. Though the hailstorm is inevitable, the catastrophe is not. This document summarizes a study of one way that homeowners and insurers can prevent costly hail damage: by using impact-resistant asphalt shingle roofs instead of standard shingles. Impact-resistant roof shingles look like ordinary shingles, but have material that makes them resistant to hail damage. When struck by large hailstones, they resist pits and fractures that would otherwise allow water to pool or penetrate beneath them. And they resist cosmetic damage like the loss of granules: the specks that cover the shingle surface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it