Canada’s Oil Sands Innovation Alliance: leading innovation in oil sands tailings
Bibliographic record
Abstract
Innovation flourishes at the intersection of great challenges meeting compelling solutions. Canada�s Oil Sands Innovation Alliance (COSIA) is an alliance of oil sands producers focused on accelerating the pace of improvement in environmental performance in Canada�s oil sands through collaborative action and innovation. COSIA's membership accounts for over 90% of the oil sands product in Canada. Canada�s oil sands producers are competitors and rivals; but they are also partners in a made-in-Canada collaboration model that is helping to redefine, globally, how companies can innovate together, and accelerate solution development to address some of the world�s biggest challenges. COSIA companies are working aggressively to accelerate the pace of environmental performance improvement in the oil sands. Canada�s oil sands industry is committed to reducing all aspects of its environmental footprint, reclaiming all lands affected by operations, and maintaining biodiversity. To create breakthrough science and technologies, COSIA brings together leading thinkers from industry, government, academia and the public. In addition, COSIA members themselves work together, each sharing considerable in-house expertise, innovation and intellectual property within the alliance, and dedicating substantial funds to COSIA�s many environmental performance projects. The unique characteristics of oil sands tailings provide member companies with an opportunity to seek out innovative tailings management and technology solutions for responsible and sustainable growth of this key global energy resource. This keynote address will elaborate on each of the Environmental Priority Areas (EPA), with an emphasis on the Tailings EPA. It will provide the audience with a brief history, achievements, current technical challenges, and opportunities for collaboration to close remaining knowledge and technical gaps to accelerate the pace of environmental performance improvement.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.010 |
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".