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Record W4411326877 · doi:10.4308/hjb.32.5.1185-1198

Juvenile Fish Composition and Their Growth Aspects on the East Coast of Banyuwangi, East Java, Indonesia

2025· article· en· W4411326877 on OpenAlexaff
Muhammad Faris Nazal, Charles P.H. Simanjuntak, Jonson Lumban Gaol, Fery Kurniawan, William W. L. Cheung, Gabriel Reygondeau, Lydia C. L. Teh, Ni Putu Asri Ratna Suhita

Bibliographic record

VenueHAYATI Journal of Biosciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersLembaga Pengelola Dana Pendidikan
KeywordsJavaFish <Actinopterygii>FisheryEast coastJuvenileComposition (language)GeographyEcologyBiologyComputer science

Abstract

fetched live from OpenAlex

The east coast of Banyuwangi, Bali Strait, has the potential to function as a nursery area for juvenile fish. Therefore, it is essential to research the ecology of juvenile fish resources. This study aimed to uncover the composition of juvenile fishes and their growth aspects through length-weight relationships and condition factors. We collected 9748 fish specimens from floating lift nets during April, September, December 2023, and February 2024. Identification and morphometric analysis were conducted to calculate fish juvenile assemblage composition, growth patterns from length-weight relationships, and condition factors. The study found 48 species from 26 families and 17 orders. The small pelagic fish group was the most common, including species from the Carangidae, Dorosomatidae, Spratelloididae, Engraulidae, Atherinidae, and Scombridae families in terms of the number of individuals and overall biomass. The fish growth on the east coast of Banyuwangi is optimal, with most fish species exhibiting positive allometric and isometric growth patterns. The overall condition factor of the juvenile fish is above 1.00, indicating that the health of fish resources is good. This suggests that the east coast of Banyuwangi, Bali Strait, can support the growth of fish juveniles and maintain the sustainability of fish resources.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.235

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.191
Teacher spread0.183 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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