Wa-Pa-Su project sustainability rating system: assessing sustainability in oil sands and heavy oil projects
Bibliographic record
Abstract
A number of environmental and sustainability rating systems have been developed and used around the world. This trend has been most notable in the building industry, where evolution of construction practices and concerns about environmental impact have led to the development of different environmental and sustainability assessment approaches, strategies, models, appraisals, and methodologies. The implementation of green technology and practices has brought economic, social, and environmental benefits with respect to improving sustainable development performance with an accompanying certification process. The framework for developing rating systems for building systems can be extended and applied in other industrial contexts. As global demand for energy continues to rise, unconventional petroleum extraction and production of petroleum substitutes are both becoming more necessary. Development and operation of unconventional oil projects can have considerable social, economic, and environmental impacts. For example, one the largest unconventional oil deposits in the world is the Athabasca oil sands in northern Canada. Government policy makers, industrial developers, and other stakeholders generally work together to develop oil sands projects in an environmentally responsible manner; however, the projects lack of an effective sustainable development measurement tool.
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 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 | 0.002 | 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".