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Record W4388542557 · doi:10.59900/pbelida.v2i2.92

POTENSI BUDIDAYA UDANG GALAH (Macrobrachium rosenbergii) DI DESA KUALA PEMBUANG I, KECAMATAN SERUYAN HILIR, KABUPATEN SERUYAN, PROVINSI KALIMANTAN TENGAH

2023· article· id· W4388542557 on OpenAlexaff
Tina Purnamasari

Bibliographic record

VenueJurnal Penelitian Belida Indonesia · 2023
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsToxicologyBiology

Abstract

fetched live from OpenAlex

Udang galah merupakan komoditas udang yang memiliki harga ekonomis dan merupakan udang terbesar dibanding dengan udang jenis lain. Udang galah memiliki 2 habitat yaitu air tawar dan air payau dengan air tawar untuk pembesaran sedangkan air payau digunakan untuk pembenihan udang galah. Tujuan dari penelitian ini adalah untuk mengetahui apakah Sungai Seruyan yang di wilayah Kecamatan Seruyan Hilir Kabupaten Seruyan Kalimantan Tengah berpotensi untuk budidaya udang galah. Berdasarkan letak geografis Sungai Seruyan di wilayah Seruyan Hilir berpotensi untuk budidaya udang galah, karena wilayah ini memiliki habitat udang galah yang memerlukan air tawar dan air payau. Terlebih berdasarkan wawancara 15 responden penangkapan udang galah di wilayah tersebut masih banyak mendapatkan udang galah dengan alat tangkap pancing, jala, dan bubu yang merupakan alat tangkap yang ramah lingkungan, sehingga kondisi ekosistem Sungai Seruyan masiih dalam keadaan baik. Minat masyarakat pun ada yang ingin membudidayakan udang galah, namun terkendala dengan modal dan minimnya pengetahuan tentang teknik budidaya udang galah. Selain itu, belum ada perhatian Dinas terkait dengan pelatihan budidaya udang galah dan menjaga ekosistem perairan di Sungai Seruyan. Berdasarkan potensi tersebut maka perlu adanya penelitian lanjutan terkait dengan kualitas air yang optimum di Sungai Seruyan.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.027
GPT teacher head0.239
Teacher spread0.212 · 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 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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