Empirically Calibrated Ground-Motion Prediction Equation for Oklahoma
Bibliographic record
Abstract
Correction| June 16, 2020 Empirically Calibrated Ground‐Motion Prediction Equation for Oklahoma Mark Novakovic; Mark Novakovic * *Corresponding author: marknovakovic@nanometrics.ca Search for other works by this author on: GSW Google Scholar Gail Marie Atkinson; Gail Marie Atkinson Search for other works by this author on: GSW Google Scholar Karen Assatourians Karen Assatourians Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2020) 110 (4): 1996–1998. https://doi.org/10.1785/0120200158 Article history first online: 16 Jun 2020 Connected Content Errata: Empirically Calibrated Ground‐Motion Prediction Equation for Oklahoma Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Search Site Citation Mark Novakovic, Gail Marie Atkinson, Karen Assatourians; Empirically Calibrated Ground‐Motion Prediction Equation for Oklahoma. Bulletin of the Seismological Society of America 2020;; 110 (4): 1996–1998. doi: https://doi.org/10.1785/0120200158 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search There is an error in equation (13) and Figure 13 of Novakovic et al. (2017), which describes the calibration factor of our ground‐motion prediction equation (GMPE). The correct equation is (13)COK={0.45for f<0.7 Hz1.54(log10(f))2−1.69(log10(f))+0.15for 0.7 Hz≤f<11.3 Hz0.08for f≥11.3 Hz.There was also a formatting error that caused values in the lower right corner of Table A3 to print in the incorrect... View Original Article You do not currently have access to this article.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".