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Record W4385721512 · doi:10.29244/jmf.v14i1.45714

Evaluasi Pengelolaan Perikanan Cumi-Cumi Skala Kecil dengan Pendekatan Ekosistem di Perairan Medan, Sumatera Utara

2023· article· id· W4385721512 on OpenAlexaff
Wini Aafini J Harahap, Zairion, Mohammad Mukhlis Kamal, Luky Adrianto

Bibliographic record

VenueMarine Fisheries Journal of Marine Fisheries Technology and Management · 2023
Typearticle
Languageid
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Perairan Laut Medan merupakan bagian dari Wilayah Pengelolaan Perikanan Indonesia (WPP 571) yang merupakan daerah penangkapan cumi-cumi ( Uroteuthis spp.) oleh nelayan skala kecil di Belawan Kota Medan. Informasi mengenai kondisi perikanan cumi-cumi di daerah ini masih sangat kurang, sehingga diperlukan kajian ilmiah untuk mengetahui status perikanan dan pengelolaannya dengan menggunakan beberapa pendekatan yang relevan. Tujuan dari penelitian ini adalah untuk mengkaji kondisi perikanan cumi-cumi yang ada di Belawan Kota Medan melalui enam domain indikator dalam Ecosystem Approach to Fisheries Management(EAFM) yaitu (1) Sumberdaya Ikan, (2) Habitat dan Ekosistem, (3) Teknik Penangkapan, (4) Ekonomi, (5) Sosial, (6) Kelembagaan. Pengambilan data untuk domain sumberdaya ikan dilakukan dengan teknik pengambilan sampel cumi-cumi secara langsung, selanjutnya data domain sosial dan ekonomi diperoleh melalui wawancara dengan kuisioner, sedangkan domain habitat dan kelembagaan dengan data sekunder. Nilai Domain tertinggi pada domain teknik penangkapan ikan sebesar 280 dengan kategori baik dan domain terendah pada domain habitat dan ekosistem sebesar 170 kategori kurang. Alasannya adalah tidak diketahui secara spesifik habitat cumi-cumi (tempat pemijahan ,daerah mencari makan dan daerah asuhan) di daerah penelitian. Sementara itu, hasil perhitungan agregat semua domain EAFM Belawan-Medan adalah 207 dalam kategori sedang , sehingga diperlukan beberapa keputusan taktis dalam pengelolaan perikanan cumi-cumi di wilayah ini.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.011
Research integrity0.0010.001
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 head0.011
GPT teacher head0.214
Teacher spread0.202 · 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 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
Published2023
Admission routes1
Has abstractyes

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