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Preface

2021· article· en· W4205280810 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessFisheries ResearchFisheries scienceSustainabilityFisheries lawFisheries managementFisheryGovernment (linguistics)AquaculturePolitical scienceFishingFish <Actinopterygii>BiologyEcology

Abstract

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Abstract Pandemic COVID-19 has hardly impacted global fisheries and aquaculture, as FAO reported in the 34th session of the Committee on Fisheries (COFI) in February 2021. FAO further suggests that this pandemic impact catalyzes the fisheries sector to be more innovative, socially, and environmentally responsible. Fish and fisheries products are well-known healthy food. It contains high quality and quantity of protein and provides essential vitamins and minerals to maintain human health status. The innovation of science and technology in the fisheries sector is a crucial point to improve and assure the efficiency and sustainability of the production and utilization of the resource. Research activities and development should be synergically conducted to implement technologies that benefit the communities. Department of Fisheries, Faculty of Agriculture, Universitas Gadjah Mada, holds a biennially international symposium to provide access and exchange of research data and fisheries experience to support the transfer of knowledge and technology to strengthen the world’s fisheries sector. The 4th International Symposium on Marine and Fisheries Research (The 4 th ISMFR) aims to bring together academic scientists, researchers, government institutions, private parties, and stakeholders to share and exchange progress information, experiences, and research results in all aspects of marine and fisheries sciences. The 4th ISMFR theme was promoting sustainable fisheries through technology and research innovation for a healthy community”. It covered a broad spectrum of fisheries-related topics, including aquaculture, fish disease, fish genetics, biotechnology, marine natural product, seafood processing technology, seafood safety, fisheries biology, fisheries resources management, fisheries socio-economics, oceanography, climate sciences, and marine ecotoxicology. Due to the Pandemic COVID-19, the 4th ISMFR was held virtual on July 28-29, 2021, by using the Zoom Meeting platform. We cannot postpone this symposium because it is a routine schedule for researchers and stakeholders to disseminate and discuss their research findings. The seminar’s organizing committee was located in the Fisheries Department, Faculty of Agriculture, Gadjah Mada University, Yogyakarta, Indonesia. Management of the symposium was carried out using the website (http://ismfr-ugm.org/). The symposium consists of a plenary session and parallel presentation sessions. The plenary session presented three keynote speakers, namely Professor Rashid Sumaila from The University of British Columbia (Canada), Professor Erlinda R. Cruz Lacierda from The University of the Philippines Visayas (Philippines), and Professor Soottawat Benjakul from The Prince of Songkla University (Thailand). A total of six parallel presentation sessions was conducted with 12 invited speakers and presenters from eight countries, namely Norway, Belgium, New Zealand, Japan, Australia, Thailand, Malaysia, and Indonesia. Presentations in each parallel class were divided into presentation panels consisting of approximately five presenters. Each presenter was given 10 minutes for presentation and discussion. Discussion sessions were held at the end of each forum for about 15 minutes. A total of 146 scientific papers have been presented at the 4th ISMFR. The 4 th ISMFR was attended by 155 participants. All presenters and attendances join the symposium virtually from their respective residences. Readers can access recordings of the 4 th ISMFR Plenary session on the YouTube channel (https://www.youtube.com/watch?v=dGtjnoR3hSo&amp;t=7599s). This proceeding provides an opportunity for readers to gain more information from the reviewed papers that have been presented in the 4th ISMFR. The articles published in this proceeding were selected from the papers presented in the symposium. The reviewers from six countries (Philippines, Egypt, Malaysia, Thailand, Japan, Indonesia) and the editors from four countries (Malaysia, Thailand, Japan, Indonesia) have participated in the abstracts screening, improving, and finalizing the manuscripts. The proceedings divided into three sections, namely aquaculture, aquatic resource management, and fish product technology. From this proceeding, readers will find recent research finding on broad aspects of fisheries and marine sciences to come up with new knowledge and idea to promote sustainable fisheries through technology and research innovation for a healthy community. We want to thank all parties for the success of the 4th ISMFR. Our gratitude is presented to the organizing committee, keynote and invited speakers, reviewers, editors, and editing staff for the dedication, hard work, and tireless efforts in implementing the symposium and publication process. We express our acknowledgment to the Rector of Universitas Gadjah Mada, the Dean of the Faculty of Agriculture, the Head of Fisheries Department, and the Publication Agency of Universitas Gadjah Mada, who provided continuous support on the symposium. Our thank you also conveyed to the speakers and participants, who have given their best efforts to disseminate, discuss, and publish papers. We also thank all parties who have contributed to the success of the 4 th ISMFR and the publication. We sincerely hope readers will find notable pieces of knowledge on fisheries and marine science from different points of view. Chief Editor List of committees of the 4 th ISMFR, List of Editors of the 4 th ISMFR proceeding, Documentation of the 4 th ISMFR 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.993

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.008
GPT teacher head0.183
Teacher spread0.174 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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