Goldset(c): Application of a Sustainability Decision Support Tool to the Roof Asphalt Shingles Recycling Project of Metro Vancouver
Bibliographic record
Abstract
Asphalt shingles constitute approximately 2% of the total waste currently disposed in the Metro Vancouver region, which corresponds to between 60,000 and 80,000 metric tonnes per year. Developing alternative uses for asphalt shingles would help the Metro Vancouver region achieve the Zero Waste Challenge and the Sustainable Region Initiative's goal of 70% waste diversion by 2015. Metro Vancouver (MV) has mandated Golder Associates Ltd (Golder) to conduct a feasibility study for the use of reclaimed asphalt shingles (RAS) in road construction. In the last decade, several trials have been performed to use RAS as an input for pavement mix across North America. MV has expressed an interest in performing an integrated sustainability assessment for economic, social, environmental as well as technical aspects of using processed RAS in road construction. This assessment is conducted using the Golder Sustainable Evaluation Tool (GoldSET), an innovative, simple Multi-Criteria Analysis (MCA) tool based on the principles of sustainable development. GoldSET has been customized to compare different options of asphalt mix: pavement containing only virgin asphalt cement, pavement containing recycled asphalt pavement (RAP), and pavement containing different ratios of RAS and RAP.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".