Bibliographic record
Abstract
The 5th International Conference on Earthquake Engineering and Disaster Mitigation, ICEEDM 2022, was held on 28th-29th September 2022. The 5th ICEEDM in Gadjah Mada University was profoundly enjoying the collaboration with the joint-organizing committee with the Indonesian Earthquake Engineering Association (AARGI), International Association for Earthquake Engineering (IAEE), Japan Association for Earthquake Engineering (JAEE), Bandung Institute of Technology, Indonesian Islamic University, and Atmajaya University. The conference was supported by a scientific committee from four countries and twelve keynote speakers from five countries, i.e., Canada, Indonesia, Japan, Taiwan, and the USA. The 5th ICEEDM 2022 was held to provide an opportunity to share experiences and disseminate the latest research and development results related to earthquake engineering, which will be very useful for increasing knowledge and disaster mitigation policies. It is hoped that this conference will benefit all parties to minimize the risk of earthquake hazards in Indonesia and worldwide. The 5th ICEEDM 2022 proceeding contains papers written by academics, professionals, researchers, and students from Indonesia and Japan. Various research works related to the conference theme were presented during the conference. A total of 41 full papers accepted upon review for the proceeding publication are categorized into the following topics: A. Structural Engineering, including; Structural Earthquake Engineering, Structural Dynamics, Performance-Based Design and Evaluation, Structural Assessment and Retrofit, Seismic Devices and Applications, Non-engineered Buildings, Experimental & Numerical Modelling B. Geotechnical Engineering, including; Geotechnical Earthquake Engineering, Soil-Structure Interaction C. Seismological Engineering, including; Seismic Micro-zonation, Case Histories in Recent Earthquakes, D. Disaster Mitigation, including; Seismic Hazard and Tsunami Disaster Mitigation, Early Warning System, Post Disaster Recovery and Reconstruction, Community-Based Disaster Risk Reduction & Management
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.614 | 0.446 |
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".