GHG Accounting in a Construction Project: The Case of Montreal's Turcot Project
Bibliographic record
Abstract
The Ministere des Transports du Quebec has undertaken the Turcot project whose central element, the Turcot Interchange, one of the most important in Quebec on which more than 300,000 vehicles travel daily, must be rebuilt. The Ministere has decided that the Turcot project should be a carbon-neutral construction project and wants the greenhouse gas (GHG) emissions linked to the construction activities to be subjected to a compensation so that the construction activities result in a carbon-neutral footprint. Since this is a new way of doing things at the Ministere and few attempts have been made with regards to construction sites in Quebec, the Ministere has developed a methodology to account for GHG emissions linked to construction activities. To do so, the first step was to identify the activities selected for measuring emissions and develop a method of accounting easy to use on worksites in order to draw a faithful portrait of GHG emissions. The first constructions for the Turcot project were carried out with traditional methods and the Ministere performed a pilot project on a worksite to account for GHG resulting from the work performed, which was expected to result in a better method of estimating GHG emissions for the overall project. The experience gained in the first constructions lots shows that accounting for GHG emissions on a construction worksite as large as that of the Turcot project presents a certain number of challenges as there are numerous sources of emissions and the activities themselves are mobile in nature. This article was also published in French as Comptabilisation des ges dans le cadre de la realisation d'un projet routier: le cas du projet Turcot a Montreal. For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".