Bibliographic record
Abstract
Currently,the design practice of highway bridges around the world are moving towards limit states design,a reliability-based design procedure.Canadian Highway Bridge Design Code(CHBDC)is the first design code entirely developed based on limit states design philosophy,including foundations and FRP components.However,reliability of a structure decreases in service due to environmental attacks and material deterioration such as fatigue,corrosion and many other reasons.Therefore,the structure should be inspected periodically,and the reliability of the structure should be evaluated according to its age and field data.If its reliability is reduced to a certain level,a repair should be scheduled as well as some preventive maintenance measures should be implemented to prevent further deterioration.Recently,many research works have been conducted to investigate reliability-deterioration mechanisms for each type of infrastructure and its components,optimize the inspection and maintenance strategy,predict remaining service life,estimate its life cycle cost.This paper is focused on the study of reliability-deterioration mechanisms of slab on steel girder bridges due to fatigue and corrosion of steel girders as well as corrosion of reinforcement in the deck slab.Examples will also be given to illustrate the proposed life cycle management strategy for composite slab on steel girder bridges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".