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Preface: 6<sup>th</sup> Astechnova International Energy Conference (ASTECHNOVA 2021)

2021· article· en· W4200595278 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)Panel discussionGlobeLibrary sciencePresentation (obstetrics)Political scienceEngineeringBusinessPsychologyMedicineComputer scienceAdvertising

Abstract

fetched live from OpenAlex

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 6 th 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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.011
GPT teacher head0.210
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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