Comparison of Alberta Industrial and Pipeline Projects and US Projects Performance
Bibliographic record
Abstract
Project performance issues are major concerns in Alberta. This paper compares the projects executed in Alberta and US projects. The paper analyses the projects performance in Alberta and compares it with US projects with a view to improve project performance in Alberta. 17 participating companies in Alberta provided the previous projects data and COAA/CII database provided the US data for the analysis. A qualitative research methodology was also employed in investigating the Alberta project performance. Interviews were conducted with industry practitioners, which contained open-ended questions. The research found that in comparison, the Alberta projects showed higher average cost and schedule growth than the US projects and the US based projects were more productive in erecting structural steel than Alberta projects. This method has the potential to contribute to a reduction in cost and schedule overruns, and improves project performance. It is concluded that comparison of projects executed in Alberta and US projects can provide a guide to companies to improve performance in Alberta.
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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) | 0.000 | 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".