A performance-based Pavement Management System for the road network of Montreal city—a conceptual framework
Bibliographic record
Abstract
Arterial roads of Montreal city, mostly constructed in 1950’s, are at an advanced state of deterioration and need major rehabilitation, upgrading, or even reconstruction. City of Montreal has allocated over $1.6 billion for road infrastructure in its 2012–2014 Three-year Capital Work Program. This investment can be wasted without proper infrastructure asset management system. The current practice of mill and asphalt overlay method by City of Montreal to rehabilitate the pavement is inadequate to repair potholes, fatigue and cracking. A performance-based pavement management system can predict the response and performance of pavement under actual dynamic traffic loads. As of today, implementations of Pavement Management Systems (PMS) are dedicated to achieve optimal levels of condition under budget restrictions. Other important objectives (e.g. mobility, safety, accessibility and social cost), along with investments to upgrade and expand the network, are normally left outside the modelling. This paper presents a conceptual framework of a dynamic PMS<br/>for the road network of Montreal City. This dynamic PMS will manage continuous aggregate behaviour of transportation system and can solve optimization problems of pavement management at any time interval.
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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 | 0.000 | 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".