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Preface

2020· article· en· W4206342352 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)Government (linguistics)ProsperityChinaPublic relationsOrder (exchange)Coronavirus disease 2019 (COVID-19)Political scienceEngineeringEngineering ethicsMedia studiesSociologyMedicineBusinessLaw

Abstract

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Currently the entire world is struggling against the virulent pandemic COVID-19. Unfortunately, each of us is affected, either directly or indirectly. Our conference, 2020 4th International Conference on Aeronautical Materials and Aerospace Engineering (AMAE 2020) was not an exception. In May, mass gatherings are not permitted by the government in China to protect people. It is uncertain when the COVID-19 would end, so it remains unclear for postponement date, while many scholars and researchers want to attend this long waited conference and have academic exchanges with their peers. Therefore, in order to actively respond the call of the government, and meet author’s request, the AMAE 2020, which was planned to be held in Chengdu, China from May 14 to 17, 2020, was changed to be held on May 15, 2020 online through Tencent VooV software. This approach not only guarantee participants’ safety and health but also meets their communication needs. Each keynote speech lasted 40 minutes, invited speech 30 minutes and author presentation 15 minutes. Each presentation was packed with questions and answers. There were lively discussion at the meeting, which promotes the academic exchange. The success and prosperity of the conference is reflected high level of the papers received. AMAE 2020 became an effective communication platform for all the participants over the world. AMAE 2020 was organized by Hong Kong Society of Mechanical Engineers. This conference aims to provide a platform for researchers and engineers to share their ideas, recent developments and successful practices in Aeronautical Materials and Aerospace Engineering. More than 70 participants attended the meeting, they were from USA, Italy, Germany, Canada, UK, Malaysia, India, Poland, Kuwait, Saudi Arabia, China and more. Five renowned speakers given speeches about their latest research and reports. They are: Prof. Ian McAndrew, Capitol Technology University, USA; Prof. Kretov Anatolii, Nanjing University of Aeronautics and Astronautics, China; Prof. Graham J. F. Hunt, Embry-Riddle Aeronautical University, USA; Assoc. Prof. Bing Li, Northwestern Polytechnical University, China and Assoc. Prof. Dmytro V. Tiniakov, Nanjing University of Aeronautics and Astronautics, China. The conference also had 2 technical sessions and 2 poster sessions. The conference proceeding is a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers 3 chapters: 1. Design; 2. Aviation; 3. Systems. We would like to acknowledge all of those who supported AMAE 2020. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the committee chairs, committee members and reviewers, for their tremendous contribution in conference organizing and peer review of the papers. We sincerely hope that AMAE 2020 will be a forum for excellent discussions that will put forward new ideas and promote collaborative researches. We are sure that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes. Finally, we would like to thank the organization and committee for all their hard work and support and hope to meet you all in person at our next conference. Prof. Ian McAndrew & Prof. Kretov Anatolii Conference Co-Chairs

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.203
Teacher spread0.160 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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