Preface: 6<sup>th</sup> Astechnova International Energy Conference (ASTECHNOVA 2021)
Bibliographic record
Abstract
Astechnova International Energy Conference (ASTECHNOVA) is an international conference that is annually organized by the Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Indonesia. This 6th ASTECHNOVA was virtually held on 24-25 August 2021 as a part of the Joint Conference EPIC-ASTECHNOVA 2021. This conference provides an ideal platform for the researchers, academicians, engineers, politicians, economists, energy enthusiasts, energy planners, and energy analysts, to share the recent research and development in the energy science discipline from various perspectives. The topics covered in this conference can be generally categorized in five (5) areas, namely new and renewable energy, energy efficiency and conservation, nuclear technology, energy security, and urban infrastructure and utilities. The joint conference was attended by approximately 500 participants from various universities and institution in Taiwan, Bangladesh, Germany, India, Japan, South Korea, Malaysia, Thailand, Canada, United States of America, Singapore, and Indonesia. The panel session of this conference includes one (1) keynote lecture and six (6) invited talks by the panel speakers from across the globe, including Japan, United States of America, United Arab Emirates, South Korea, and Indonesia. As for the parallel session, oral presentations were delivered by the authors who submit their researches. In total, ASTECHNOVA 2021 organizer accepted 48 paper submissions after reviewed by distinguished experts in the field. The reviewing process has considerably reduced the number of published papers, but it also has raised the proceedings’ quality. Finally, we would like to thank all the participants, authors, panel speakers, reviewers, panel session moderators, parallel session chairs, steering committee, organizing committee, technical coordinators, and all other supporting staff for their tremendous support during this conference. Astechnova 2021 Editorial Team List of Foreword from Rector of Universitas Gadjah Mada, Foreword from Acting Director for Non-Aligned Movement Centre for South-South Technical Cooperation (NAM CSSTC), List of Committees are available in this pdf.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.237 | 0.175 |
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".