CALCULATION OF PERFORMANCE SCORE FOR A DAMAGED RC BUILDING
Bibliographic record
Abstract
Detailed investigation of buildings was not possible because of amount of existing building stocks. Rapid assessment methods were developed to reduce stock numbers of the buildings subjected to detailed evaluation. The buildings which have priority risks can be detected with the help of these methods. Thanks to most rapid evaluation methods, it is possible to determine some of the parameters that would affect the building's behavior in case of an earthquake partially without even entering the building and partially through the data obtained from the interior of the building. This study aims to investigate the earthquake performances of Gedikbulak School building that has totally collapsed after Van earthquake. The school was located close to the epicenter of the earthquake. In this study Japan Seismic Index Method, Canadian Seismic Screening Method and P25 rapid assessment methods were used. Aim of this study is comparing the behavior of building under an earthquake and scores of rapid assessment methods. This study reveals that the rapid evaluation methods can be used conveniently
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".