Principal Component Analysis for Predicting the Response of Nonlinear Base‐Isolated Buildings
Why this work is in the frame
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Bibliographic record
Abstract
In the design of base‐isolated buildings, a critical parameter governing the selection of isolator parameters is the peak displacement of the isolation layer. In this study, a model is developed in order to predict the peak base displacements utilizing multiple ground motion parameters, called intensity measures (IMs), as the inputs. The issue of correlation between various IMs is addressed through principal component analysis (PCA). This method also lends itself to dimensionality reduction, as those components that do not contribute significantly to the variance are discarded. The prediction intervals from the model are compared with the results from nonlinear dynamic analysis. An important conclusion is that by using the PCA based model, the standard errors remain relatively small and constant for a wide range of isolation periods. It is therefore clear that by utilizing multiple IMs and accounting for their correlation effects, it is possible to estimate the responses of base‐isolated buildings with good confidence.
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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 | 0.001 |
| 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) | 0.000 | 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