Final design report for roof shingle made from ground tire rubber (GTR) fibres to withstand Winnipeg weather
Bibliographic record
Abstract
The objective of this project was to design a shingle using recycled ground tire rubber capable of withstanding Winnipeg, MB weather conditions. Our team developed and tested various rubber and additive mixtures to assess their strength and durability under specific conditions. Of the mixtures that seemed promising during initial testing phases, they were then subjected to weather simulations representing 1 in 25-year storm conditions in Winnipeg. The final stage involved creating full-scale prototypes using a mold designed by the team, which ultimately determined the project’s success. Despite initial promising results, unexpected failures occurred during the full-scale production phase, resulting in inconclusive findings regarding shingle viability. Further testing and refinement are necessary to meet the client’s requirements and to address the challenges that were encountered during this project. Recommendations for future research and improvements include optimizing the materials used, enhancing the appearance of the shingles to better suit the aesthetic desires of the client, improve efficiency by manufacturing a different mold, process optimization such as incorporating an injection mold and exploring liquid mixture formulations, and researching the feasibility and economic factors in mass-producing shingles using the proposed materials.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".