Unified modelling of infrastructure asset performance deterioration – a bounded gamma process approach
Why this work is in the frame
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Bibliographic record
Abstract
Infrastructure asset management systems require a flexible deterioration model that can handle various degradation patterns in a unified way. Due to their appealing monotonic sample paths, independent increments, and mathematical tractability, gamma processes have been widely employed as a model for infrastructure performance deterioration. This model was recently enhanced by introducing an upper bound to satisfy a practical modelling need that physical or managerial limits constrain many deterioration processes. Several bounded transformed gamma process (BTGP) alternatives had been proposed; however, they lacked sufficient flexibility to characterise different deterioration patterns. This paper proposed a new BTGP model that is deeply rooted in the traditional regression modelling widely used in most infrastructure asset management systems. Qualitative and quantitative comparisons were carried out between the proposed BTGP and a bounded nonstationary gamma process (BNGP) model from both deterioration modelling and asset management decision-making perspectives. An empirical study using real-world historical bridge condition data was conducted to examine the flexibility of the BTGP compared to the BNGP and six other BTGP alternatives. The results confirmed the flexibility and significance of the proposed BTGP model for infrastructure systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it