Preliminary evaluation of Pier cap from an ASR affected bridge in Central Canada
Bibliographic record
Abstract
The Bridge, a highway bridge structure, was built using a suspected alkali-silica reactive aggregate in the 1960’s in a city in central Canada. Its concrete elements experienced rapid deterioration resulting in the need for costly increased repairs and rehabilitations. Alkali-silica reaction (ASR) is one of several damage mechanisms which might be contributing to damage of concrete elements. Infrastructure in central Canada experiences frequent freeze-thaw cycles, and heavy use of de-icing salts in winter as well as high heat and humidity in summer which might intensify distress. In recent years several concrete elements were selected for further assessment. Among them, five segments of a decommissioned Pier cap were selected for preliminary evaluation through visual inspection (conventional, semi-quantitative and quantitative using the cracking index) and non-destructive techniques (Schmidt hammer, ultrasonic pulse velocity and surface resistivity). Preliminary assessment results will be used to determine the appropriate locations (i.e., demonstrating the lowest/ highest deterioration) to extract cores for further assessment. Future work will be conducted on extracted cores using a multi-level assessment technique consisting of mechanical (compressive testing and stiffness-damage test) and microscopic procedures (the damage rating index and SEM) to assess the condition of the Pier cap.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".