Summary of the Discussions During the 2023 SSA Topical Meeting on “Future Directions for Physics-Based Ground Motion Modeling”
Bibliographic record
Abstract
Calendar| March 29, 2024 Early Publication Meeting Reports Hiroshi Kawase; Hiroshi Kawase 1Disaster Prevention Research Institute, Kyoto University, Uji, Japan2General Building Research Corporation of Japan, Osaka, Japan Search for other works by this author on: GSW Google Scholar Annemarie Baltay Annemarie Baltay * 2GU.S. Geological Survey, Earthquake Science Center, Mountain View, California, U.S.A. *Corresponding author: abaltay@usgs.gov Search for other works by this author on: GSW Google Scholar Author and Article Information Hiroshi Kawase 1Disaster Prevention Research Institute, Kyoto University, Uji, Japan2General Building Research Corporation of Japan, Osaka, Japan Annemarie Baltay * 2GU.S. Geological Survey, Earthquake Science Center, Mountain View, California, U.S.A. *Corresponding author: abaltay@usgs.gov Publisher: Seismological Society of America First Online: 29 Mar 2024 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © Seismological Society of America Seismological Research Letters (2024) https://doi.org/10.1785/0220240084 Article history First Online: 29 Mar 2024 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Hiroshi Kawase, Annemarie Baltay; Meeting Reports. Seismological Research Letters 2024; doi: https://doi.org/10.1785/0220240084 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 Seismological Society of America (SSA) topical conference, Future Directions for Physics‐Based Ground Motion Modeling, was held in Vancouver, Canada, on 10–13 October 2023, co‐sponsored by the Seismological Society of Japan and co‐chaired by Annemarie Baltay of the U.S. Geological Survey and Hiroshi Kawase of Kyoto University. This meeting brought together many researchers and practitioners interested in modeling, observing, and utilizing ground‐motion models (GMMs). Scientists gathered to discuss complex kinematic and dynamic rupture simulation approaches, empirical representations of the earthquake source, site and path effects, physical modeling of the recording site, challenges for model extrapolation, and overall prediction accuracy and... 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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".