Damage assessment of semi-precast slabs using impact-echo method
Bibliographic record
Abstract
Semi-precast slabs are widely used in precast concrete constructions in China nowadays.However the construction quality of them are often hard to control, and the constructoion quality of the upper in-situ concrete of them is difficult to be guaranteed, as a result, how to detect the construction defects correctly and timely become more and more important. In this paper a traditional method Impact-Echo (IE) method is used to detect the flaws between the precast concrete and the upper in-situ concrete of the semi-precast slabs. Firstly one experimental slabs with many designed flaws was constructed, and than IE method was used to detect these flaws, fially the detected results were analysed to evaluate the proposed method. The results were processed using a mapping strategy, which indicated suspicious points where core extraction was undertaken. All cores taken from points derived from IE method results were found to have flaws providing evidence. The experimental results show that IE method may be a suitable tool to assess the construction quality of Semi-precast slabs
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".