Large-Scale Testing of Low-Ductility, Concentrically-Braced Frames
Bibliographic record
Abstract
In regions of moderate seismic hazard, the costly structural detailing necessary to ensure adequate ductile performance of a braced frame during an earthquake event can be difficult to justify economically. Structural engineers, however, are permitted to design low-ductility systems if larger demands are assumed. In regions of moderate seismic hazard, this philosophy has proved to be economical and has resulted in widespread use of such low-ductility braced frame systems. Despite this popularity, the inelastic behavior and collapse performance of these systems are not currently understood at a fundamental level. A broadened understanding of the inelastic behavior of low-ductility braced frames can lead to an improved seismic design philosophy and provide practicing structural engineers with a coherent, rational, and transparent design approach applicable to moderate seismic regions. This research aims to identify low-ductility braced frame failure mechanisms and the sequence in which they occur, as well as to draw conclusions on the implications of the observed behavior contextually in building collapse performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".