Bibliographic record
Abstract
It is with great pleasure that we present the proceedings of the 20th International Conference on Ground Penetrating Radar (GPR, 2024), held from June 23-27, 2024, at Jilin University in Changchun, China. This conference, organized by Jilin University and the Chinese Geophysical Society, it is the second time this prestigious event has been hosted in mainland China. The theme of this year’s conference, “GPR for Better City,” reflects our focus on leveraging GPR technology to enhance urban life and development. The conference was remarkable, bringing together over 330 participants from 21 countries and regions, including 64 international delegates. The conference featured 104 oral presentations, 55 poster sessions, and specialized short courses on Gprmax GPR numerical simulation software and Geotilx GPR data processing, attracting over 80 experts and scholars. The conference also hosted an exhibition showcasing the latest GPR instruments and software, with participation from 14 organizations and manufacturers from China, Russia, the United States, Canada, South Korea, and Latvia. We were honored to have seven distinguished scholars, including experts from Japan, the Netherlands, Belgium, and China, deliver keynote and plenary speeches. Their presentations covered various topics, such as advancements in electromagnetic theory for understanding GPR signals, progress in underground structure detection using navigation and communication satellite signals, and new developments in UAV-mounted GPR systems. Additionally, the latest achievements in China’s “Chang’e 6” lunar mission and “Tianwen-2” Mars mission were shared, sparking lively discussions among participants. We extend our heartfelt thanks to all the authors who contributed their work, the keynote speakers who shared their valuable insights, and the reviewers who ensured the high quality of the contributions. Special appreciation goes to the organizing and technical program committees for their dedication and hard work in bringing this conference to fruition. The papers included in this volume will serve as a significant resource for GPR researchers, practitioners, and enthusiasts, contributing to the continued advancement of GPR technology. We also hope that GPR 2024 has fostered new collaborations and research initiatives that will drive innovation in this field for years. We look forward to welcoming you to future editions of the GPR International Conference, where we will continue to explore and develop this vital technology for society’s benefit. The Committee of GPR 2024 list of Organizing Committees are available in this Pdf.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| 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) | 0.528 | 0.377 |
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".