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Preface

2020· article· en· W4243852512 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChinaExcellenceLibrary scienceCommercializationEngineeringPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

Previous ICESCE conferences were held in Shenzhen, Kunming, Haikou (China), Shenzhen from 2015-2019. In light of the worldwide spread of COVID-19, the conference organizing committee has decided to postpone the 6th edition conference to July 17-19, 2020 in Dali, China for the safety and health of all the participants. The 2020 6th International Conference on Energy Science and Chemical Engineering (ICESCE 2020) is to bring together innovative academics and industrial experts in the field of energy science and chemical engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in energy science and chemical engineering and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The meeting focused on the latest research fields of “Energy Science” and “Chemical Engineering”. It consists of two parts: speeches of keynote speakers and oral presentations. More than 100 participants attended the meeting, they were from China, Bulgarian, Canada, India, South Africa, Italy, Ireland and more. In the first part, we invited two professors as our keynote speakers. Prof. Lei Xing, Institute of Green Chemistry and Chemical Engineering, Jiangsu University, China as well as our conference chair. He performed a speech on Functionally graded electrodes and segmented design toward the commercialization of PEM (proton exchange membrane) fuel cells. His research on PEM fuel cells improved cell performance. Assoc. Prof. Md. Hasanuzzaman, Higher Institution Centre of Excellence (HICoE), University of Malaya, Malaysia. He talked about Global Challenges in the Energy Sector: Prospects of Solar Thermal Energy . He appealed to make full use of the solar thermal energy to slow down the global warming and climate change. Their insightful speeches had triggered heated discussion in the second session of the conference. Every participant praised this conference for disseminating useful and insightful knowledge. List of Conference Chair, Organizing Committee and Technical Committee 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.578
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.274
Teacher spread0.222 · 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 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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