Data for Nonstructural Design Requirements for Functional Recovery Performance, in Development of Recovery-Based Seismic Design Requirements for the 2026 NEHRP Provisions
Bibliographic record
Abstract
In the move toward design practices that facilitate recovery, there are ongoing efforts to reevaluate structural seismic design parameters such as design drift limits and response modification coefficients. These datasets are the product of work to support the development of the 2026 National Earthquake Hazards Reduction Program (NEHRP ) functional recovery design provisions. We proposed structural design requirements that limit the occurrence of safety-critical structural damage, i.e., damage that must be repaired for occupants to return to a building safely (Blowes et al., 2025a). We also proposed nonstructural design requirements for functional recovery (Blowes et al., 2025b) by evaluating the probability of meeting recovery time targets set by the Building Seismic Safety Council. The design checks are performed at a new risk-targeted Functional Recovery Earthquake (FRER) that follows a similar structure to current ASCE 7 Chapter 12 life-safety requirements. These datasets provide key inputs and outputs (e.g., engineering demand parameters, component fragilities, safety-critical structural damage data, recovery time data) from the calculations underpinning the 2026 NEHRP functional recovery provisions.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.032 |
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".