AN ECONOMIC IMPACT ANALYSIS OF SUNCOR’S MONTREAL REFINERY IN MONTREAL AND QUEBEC Prepared for Suncor Energy By
Bibliographic record
Abstract
economic, financial, and business strategy consulting firm with more than 550 professionals in 11 offices in North America and internationally in Beijing. The Montreal office specializes in engagements that require strong analytical and statistical capabilities. We frequently deliver modeling and statistical analyses led by prominent Canadian and American academics, including French-speaking experts. In recent years, our economists and statisticians have been involved in several highly technical and data-intensive cases that have required both extensive theoretical modeling and comprehensive statistical analyses. Groupe d’analyse also offers consulting services in strategy and expertise on matters of litigation, public policy, financial economics, health economics and program evaluation. We have played a leading role in many complex litigation matters involving finance, competition, commercial litigation, and patent infringements. Our reports have often been presented before parliamentary committees in Quebec and Ottawa, North American courts, regulators and the media. For further information, visit www.groupedanalyse.ca
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".