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Record W4391896393 · doi:10.61992/jpb.v2i1.60

SOSIALISASI HASIL TANGKAPAN IKAN CAKALANG PADA KAPAL 20-60 GT di PANGKALAN PENDARATAN IKAN (PPI) MEUREDU, KABUPATEN PIDIE JAYA

2023· article· id· W4391896393 on OpenAlexaff
Wulan Agustria, Thaib Rizwan, Ilham Zulfahmi, Ichsan Setiawan, Sayyid Afdhal El Rahimi, Yulizar, Razali Thaib, Muhammad Arief, Syarifah Meurah Yuni, Husaini Husaini, Ratna Mutia Aprilla

Bibliographic record

VenueJurnal Pengabdian Bangsa · 2023
Typearticle
Languageid
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsFisheryPhysicsBiology

Abstract

fetched live from OpenAlex

pengabdian ini bertujuan untuk mesosialisasi hasil tangkapan ikan cakalang (Katsuwonus pelamis) pada pangkalan pendaratan ikan (PPI) Mereudu, Kabupaten Pidie Jaya yang menggunakan alat tangkap Purse seine. Pengambilan data yang dilakukan dalam penelitian ini adalah menggunakan metode observasi lapangan dengan melakukan pengamatan langsung kegiatan di Pangkalan Pendaratan Ikan ( PPI) Mereudu Pidie Jaya serta melakukan wawancara kepada pihak yang terlibat di dalam nya . Trip penagkapan yang dilakukan oleh para nelayan pidie jaya berkisar antara 5 hari menurut hasil tangkapan yang sudah di dapatkan apabila hasil tangkapan sudah sampai dengan target maka para nelayan langsung kembali meskipun belum sampai 5 hari. Selama penelitian jumlah hasil tangkapan ikan cakalang terbanyak terdapat pada tanggal 27 juli 2022 dengan hasil tangkapan sebanyak 5.000 kg dan untuk hasil tangkapan terendah pada tanggal 29 juli 2022 dengan hasil tangkapannya sebanyak 1,500 kg

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), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.017

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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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 designNot applicable
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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