A CASE STUDY IN THE APPLICATION OF PROJECT LEVEL LIFE CYCLE ANALYSIS TO ASPHALT PAVEMENT PRESERVATION STRATEGIES: A CANADIAN CASE STUDY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper covers a Canadian project that commenced in 1997 and was successfully completed in 1998. This paper discusses the development of a method to use network level pavement management system (PMS) data for life cycle costing analysis of pavement preservation strategies. The method was applied successfully to the variety of pavement conditions and structures making up the primary highway network in the Province of Saskatchewan. This project followed a project that implemented probabilistic and deterministic network level PMS within Saskatchewan Highways and Transportation. The project discussed in this paper was to determine the whole of life implications for different treatment strategies on paved roadways using PMS data. The methodology was applied to asphalt pavements and to other road surface structures. The paper discusses the details of the method and the network level data used on the asphalt pavement portion of the project. The paper includes: (1) description of the network level probabilistic cost/deterioration models; (2) description of network level deterministic deterioration models; (3) how the models were combined to develop deterministic project level deterioration versus maintenance cost model; (4) application of the project level models in life cycle cause and effect models; (5) the method used to analyze the above to develop net present worth and equivalent annualized cash flow for different level of service starting case scenarios. (a) For the covering entry of this conference, please see ITRD abstract no. E202467.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| 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) | 0.000 | 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 it