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Record W4403616640 · doi:10.33512/jpk.v14i1.27697

The Utilization Pattern of Capture Fisheries in the Limited Utilization Zone of the Gili Matra Marine Protected Area in West Nusa Tenggara Province

2024· article· en· W4403616640 on OpenAlexaff
Rowi Ashari, Soraya Gigentika, Sitti Hilyana, Martanina Martanina

Bibliographic record

VenueJurnal Perikanan dan Kelautan · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsFisheryMarine protected areaEnvironmental scienceForestryGeographyEnvironmental protectionEcologyBiology

Abstract

fetched live from OpenAlex

location for capture fisheries activities. However, the management has not yet assessed the area's utilization for capture fisheries activities, necessitating research on the utilization pattern of capture fisheries in the Gili Matra conservation area. This research aims to identify the types of fishing gear used and analyze the size of the dominant fish caught in the Gili Matra marine protected area. This research was conducted from February to April 2024. Data were collected through interviews with respondents and by measuring the length of the fish. The respondents in this study were groups of fishermen who caught fish within the limited utilization zone, selected using the accidental sampling method. The number of fish samples measured in this study was 30 individuals for each fish species. The fish species measured were the dominant species caught in the Gili Matra marine protected area. The data were analyzed using descriptive analysis and length frequency analysis. The study results showed fishermen use bottom handlines, gillnets, and spearguns to catch fish within the limited utilization zone in the Gili Matra marine protected area. The dominant fish species caught in the area were Lutjanus gibbus , Siganus virgatus , and Parepeneus indicus . Almost all of these fish species had capture sizes larger than the length at first maturity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.214
Teacher spread0.197 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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