A risk-based approach to corrosion protection and maintenance of steel bridges
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
<p>A computer-based decision making tool used to minimize the cost of coating maintenance for steel bridges is presented. Variations of the model, adapted for specific usage, are presented. A maintenance approach with the lowest equivalent uniform annual cost is recommended for each analysis using the model. The analysis may be performed for a single bridge structure using deterministic or probabilistic input values, or for many bridge structures of a certain inventory using deterministic input values. Using the model to analyze the entire bridge inventory provides an estimation of the annual budgetary requirements for the coating maintenance in a region and will facilitate the prioritization of these coating maintenance projects. The paper focuses on state-of-theart practices in corrosion protection coating maintenance in the Province of British Columbia, Canada.</p>
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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 | 0.001 | 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 it