Data set from shaking table tests of a slender MDOF structure with base‐rocking mechanisms
Bibliographic record
Abstract
Numerical models of seismic‐resistant structures are typically validated by comparing numerically predicted key seismic response parameters to those obtained from benchmark shake table experiments. However, studies have shown that for structures rocking on rigid foundations, the seismic response can be unrepeatable in experiments and deterministically unpredictable by numerical models. Therefore, researchers have proposed to validate rigid rocking models using statistical approaches, yet no experimental study has examined whether the same observations apply to slender multi‐degree‐of‐freedom (MDOF) free‐rocking structures or controlled rocking structures with positive post‐rocking stiffness and dedicated energy dissipation. This data paper describes the now publicly available data obtained from a series of 254 shaking table tests of a slender MDOF tower structure with two base‐rocking mechanisms, which can be used to examine the predictability of the seismic response of an MDOF rocking structure and to statistically validate different approaches aiming to model tall and slender structures that utilize base‐rocking mechanisms to mitigate the dynamic response due to higher‐mode effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".