A Methodology for Probabilistic Fault Displacement Hazard Analysis (PFDHA)
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Bibliographic record
Abstract
We present a methodology for conducting a site‐specific probabilistic analysis of fault displacement hazard. Two approaches are outlined. The first relates the occurrence of fault displacement at or near the ground surface to the occurrence of earthquakes in the same manner as is done in a standard probabilistic seismic hazard analysis (PSHA) for ground shaking. The methodology for this approach is taken directly from PSHA methodology with the ground‐motion attenuation function replaced by a fault displacement attenuation function. In the second approach, the rate of displacement events and the distribution for fault displacement are derived directly from the characteristics of the faults or geologic features at the site of interest. The methodology for probabilistic fault displacement hazard analysis (PFDHA) was developed for a normal faulting environment and the probability distributions we present may have general application in similar tectonic regions. In addition, the general methodology is applicable to any region and we indicate the type of data needed to apply the methodology elsewhere.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.006 | 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