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ICSAEES 2024 Preface

2024· article· en· W4405615874 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCOVID-19 impact on air quality
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The First International Conference on Sustainable Applied Earth and Environmental Sciences (ICSAEES 2024) was held in hybrid mode at the Lakesource Publishing Company Conference Hall, Ikate Lekki, Lagos, Nigeria, from 27 th to 29 th August, 2024. ICSAEES 2024 is the maiden edition of the annual international conference initiated by the Society of Sustainable Applied Earth and Environmental Sciences (SSAEES) in collabration with the Lakesource Publishing Company (LPC). The aim of this conference is to gather new research contributions from all disciplines of Applied Renewable Energy and Environmental Earth Sciences by scientists from diverse backgrounds, and thus makes an essential contribution towards ensuring that science and technology contribute to the promotion of a more sustainable environment from different parts of the world. It is our belief that the proceedings in ICSAEES would help to address the numerous local and national challenges that are relevant to the realisation of the United Nation’s “Global Goals” generally referred to as Sustainable Development Goals (SDGs). The SDGs were crafted with the intention of ensuring better quality life, peace and prosperity for all people, as well as protecting and preserving our environment and planet in general. We appreciate all our Keynote Speakers: Prof. Mohammad Alam Saeed (Vice-Chancellor, University of Education, Lahore, Pakistan), Prof. K. Srinivas Reddy (Institute of Technology Madras, Chennai, India), Prof. Anand K. Plappally (Indian Institute of Technology, Jodhpur, India), Dr. Masood Yousaf (University of Education, Lahore, Pakistan), Dr. Anil Kumar (Delhi Technological University, Delhi, India), Dr. M. V. Reddy (Energy Storage Technology, New Graphite World, Quebec, Montreal, Canada) and Dr. Babatunde Abiodun Obadele (Botswana International University of Science and Technology, Palapye, Botswana; & University of Johannesburg, South Africa) for honouring our invitations and for the insightful experiences they have shared during the ICSAEES 2024. The Organising Team is happy to report success in the number of papers submitted and presented in the maiden edition of the ICSAEES 2024. We received 39 papers from Nigeria, India, Indonesia, South Africa and the United Kingdom. The papers were blinded peer reviewed by number of experts and revised by the authors prior to final acceptance of 19 papers. This present volume has an acceptance rate of 48.7%. The proceedings of the ICSAEES 2024 are published in the current volume of IOP Conference Series: Earth and Environmental Science, which are divided into five (5) Sections relating to Applied Earth and Environmental aspects of the SDGs as stated on the conference website (https://icsaees.com.ng/). The Sections are Applied Renewable Energy for Sustainable Development; Applied Earth Sciences for Sustainable Development; Applied Environmental Sciences for Sustainable Development; Applied Environmental Impact Assessment for Sustainable Development; and Applied Atmospheric Studies for Sustainable Development. Various topics presented in this volume will be useful to researchers, industrialists, experts, scholars, students, among others in the fields of Science, Engineering, Social Sciences, and associated fields in connection with the sustainability related issues. List ICSAEES 2024 Committee of Directors, Scientific Committee and ICSAEES 2024 Reviewers 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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
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
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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