The SDSU Broadband Ground-Motion Generation Module BBtoolbox Version 1.5
Bibliographic record
Abstract
Research Article| December 17, 2014 The SDSU Broadband Ground‐Motion Generation Module BBtoolbox Version 1.5 Kim Olsen; Kim Olsen Department of Geological Sciences, GMCS 231A, San Diego State University, 5500 Campanile Drive, San Diego, California 92182 U.S.A.kbolsen@mail.sdsu.edu Search for other works by this author on: GSW Google Scholar Rumi Takedatsu Rumi Takedatsu Department of Geological Sciences, GMCS 231A, San Diego State University, 5500 Campanile Drive, San Diego, California 92182 U.S.A.kbolsen@mail.sdsu.edu Search for other works by this author on: GSW Google Scholar Seismological Research Letters (2015) 86 (1): 81–88. https://doi.org/10.1785/0220140102 Article history first online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Kim Olsen, Rumi Takedatsu; The SDSU Broadband Ground‐Motion Generation Module BBtoolbox Version 1.5. Seismological Research Letters 2014;; 86 (1): 81–88. doi: https://doi.org/10.1785/0220140102 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search The Southern California Earthquake Center (SCEC) has completed phase 1 of its Broadband Platform (BBP) ground‐motion simulation results, evaluating the potential applications for engineering of the resulting 0.01–10 s pseudospectral accelerations (PSAs) generated by five different methods. The exercise included part A, in which the methods were evaluated based on the bias of simulation results to observations for 12 well‐recorded historical earthquakes: 7 in the western United States, 2 in Japan, and 3 in the eastern United States/Canada. In addition, part B evaluated simulation results for Mw 5.5, 6.2, and 6.6 scenarios at 20 and 50 km from the... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.586 | 0.630 |
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".