A methodology for the estimation of kappa (κ) for large datasets. Example application to rock sites in the NGA-East database
Bibliographic record
Abstract
This report reviews four of the main approaches (two band-limited and two broadband) currently used for estimating the site κ0: the acceleration slope (AS) above the corner frequency, the displacement slope (DS) below the corner frequency, the broadband (BB) fit of the spectrum, and the response spectral shape (RESP) template. Using these four methods, estimates of κ0 for rock sites in Central Eastern North America (CENA) in the shallow crustal dataset from NGAEast are computed for distances less than 100 km. \n \n \nUsing all of the data within 100 km, the mean κ0 values are 8 msec for the AS approach and 27 msec for the DS approach. These mean values include negative κ estimates for some sites. If the negative κ values are removed, then the mean values are 25 msec and 42 msec, respectively. Stacking all spectra together led to mean κ0 values of 7 and 29 msec, respectively. Overall, the DS approach yields 2–3 times higher values than the AS, which agrees with previous observations, but the uncertainty of the estimates in each case is large. The AS approach seems consistent for magnitudes down to M3 but not below. \n \n \nThere is large within-station variability of κ that may be related to differences in distance, Q, complexity along the path, or particular source characteristics, such as higher or lower stress drop. The station-to-station differences may be due to site-related factors. Because most sites have been assigned Vs30 = 2000 m/sec, it is not possible to correlate variations in κ0 with rock stiffness. \n \n \nBased on the available profile, the individual spectra are corrected for crustal amplification and only affect results below 15 Hz. Since the AS and DS approaches are applied over different frequency ranges, we find that only the DS results are sensitive to the amplification correction. More detailed knowledge of individual near-surface profiles may have effects on AS results, too. Although κ is considered to be caused solely by damping in the shallow crust, measurement techniques often cannot separate the effects of damping and amplification, and yield the net effect of both phenomena. \n \n \nThe two broadband approaches, BB and RESP, yield similar results. The mean κ0_BB is 5±0.5 msec across all NEHRP class A sites. The κ0_RESP for the two events examined is 5 and 6 msec. From literature, the average value of κ0 in CENA is 6 ± 2 msec. This typical value is similar to the broadband estimates of this study and to the mean κAS when all available recordings are used along with all flags. When only recordings with down-going FAS slope are selected from the dataset, the mean value of κAS increases by a factor of 2–3. \n \n \nTo evaluate the scaling of high-frequency ground motion with κ, we analyze residuals from ground motion prediction equations (GMPEs) versus κ estimates. Using the κ values from the AS approach, the average trend of the ln(PSA) residuals for hard-rock data do not show the expected strong dependence on κ, but when using κ values from the DS approach, there is a stronger correlation of the residuals, i.e., a κ that is more consistent with the commonly used analytically based scaling. The κDS estimates may better reflect the damping in the shallow crust, while the κAS estimates may reflect a net effect of damping and amplification that has not been decoupled. The κDS estimates are higher than the κAS estimates, so the expected effect on the high-frequency ground motion is smaller than that expected for the κAS estimates. \n \n \nAn empirical hard-rock site factor model is developed that represents the combined Vs-κ0 site factor relative to a 760 m/sec reference-site condition. At low frequencies (< 3 Hz), the empirical site factors are consistent with the scaling due to the change in the impedance contrast. At high frequencies (> 10 Hz), the residuals do not show the strong increase in the site factors as seen in the analytical model results. A second hard-rock dataset from British Columbia, Canada, is also used. This BC hard-rock residuals show an increase in the 15–50 Hz range that is consistent with the analytical κ0 scaling for a hard-rock κ0 of about 0.015 sec. \n \n \nThe variability of the PSA residuals is also used to evaluate the κ0 scaling for hard-rock sites from analytical modeling. The scatter in existing κ0 values found in literature is disproportionately large compared to the observed variability in high-frequency ground motions. We compared the predicted ground-motion variability based on analytical modeling to the observed variability in our residuals. While the hard-rock sites are more variable at high frequencies due to the additional κ0 variability, this additional variability is much less than the variability predicted by the analytical modeling using the variability from κ0-Vs30 correlations. This is consistent with weaker κ0 scaling compared to that predicted by the analytical modelling seen in the mean residuals.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".