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Preface

2022· article· en· W4306880208 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2022
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)EngineeringGovernment (linguistics)Library scienceManagementPolitical scienceBusinessComputer science

Abstract

fetched live from OpenAlex

The conference on Sustainable Energy, Environment, and Green Technologies (ICSEEGT 2022) is the second international conference organized at Poornima College of Engineering, Jaipur, Rajasthan, India. This event was organized in a hybrid mode. This conference aims to bring researchers from academia, government agencies, research laboratories, and the corporate sector to present their research on sustainable and renewable energy, the environment, transportation engineering and green technologies. Since green growth is pursuing economic development in an environmentally sustainable manner, therefore green growth must play a vital role in the development goal of improving living standards, accessing modern energy services, and using energy more efficiently. For this aim, the conference ICSEEGT 2022 provided an excellent platform to promote research in the subject area and exchange new ideas in these fields among academicians, engineers, scientists, and practitioners across the world. The conference began with its inaugural session (in hybrid mode), seeking the blessings of Goddess Saraswati. The session witnessed addresses of dignified persons, Professor S.A Sherif, Department of Mechanical and Aerospace Engineering, University of Florida, USA, Professor L.M. Das, Former Professor, Centre for Energy Studies, Indian Institute of Technology, Delhi, India and Dr. L. N. Thakural, Senior Scientist, Surface Water Division, National Institute of Hydrology, Roorkee, India. The inaugural session was followed by a keynote session of Professor P. Muthukumar, Professor, Indian Institute of Technology, Guwahati, India, on the Energy Efficient and Environment Friendly Porous Radiant Burners for Cooking and Industrial Applications. Later, four parallel technical sessions were organized on the first day, where authors and participants participated and presented their papers. Overall, 186 research papers were received for ICSEEGT 2022 from different organizations worldwide, out of which our expert team of reviewers accepted 102 papers. The research papers in this conference were invited considering these three tracks: sustainable/renewable energy, environment and transportation, green technologies, and urban development. The presenters and attendees participated with full enthusiasm in all the technical sessions. Out of 83 registered papers, 43 papers were presented in the technical sessions on the first day. The first Technical Session in offline mode was chaired by Dr. Narayan Lal Jain and Dr. Pran Nath Dadhich, and moderated by Mr. Rahul Sharma of Poornima College of Engineering, Jaipur, India. The second Technical Session was chaired by Dr Salifu Tahiru Azeko, Tamale Technical University, Tamale, Ghana: Mr. Sanjay Kumawat, Poornima College of Engineering, was the moderator for this session. Dr. Tanuj Chopra from Thapar Institute of Engineering and Technology, Patiala, India chaired the third Technical Session. The second and third session moderator were Mr. Divya Vishnoi and Mr. Sanjay Kumawat, Poornima College of Engineering respectively. Dr. Puneet Kumar Jain, National Institute of Technology, Raurkela, and Dr. Ram Niwash Mahia, National Institute of Technology, Hamirpur, India chaired the fourth Technical Session and moderated Dr. Monika Vardia from Poornima College of Engineering. The day ended with a keynote session on Recent Advances Materials on Energy Storage Technology and Sustainability by Dr. M V Reddy, Senior Professional Researcher, Nouveau Monde Graphite (New graphite world) (NMG), Quebec, Montreal, Canada. 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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.590
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.5900.422

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 head0.198
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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