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Record W4250082228 · doi:10.31230/osf.io/382bv

Ekosistem terumbu karang di Pulau Maputi, Kabupaten Donggala, Provinsi Sulawesi Tengah

2018· preprint· id· W4250082228 on OpenAlexaff
Samliok Ndobe, Abigail Mary Moore, Deddy Wahyudi, Muslihuddin, Mohammad Rizki Akbar

Bibliographic record

Venuenot available
Typepreprint
Languageid
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesForestryGeographyArt

Abstract

fetched live from OpenAlex

Pulau Maputi di Selat Makassar, Kabupaten Donggala, Provinsi Sulawesi Tengah merupakan salah satu pulau yang memiliki nilai keanekaragaman hayati tinggi, antara lain sebagai tempat bertelur penyu hijau. Untuk mengetahui kondisi ekosistem di Pulau tersebut, pada tahun 2013 dilakukan penelitian survei, terutama survei ekosistem terumbu karang untuk penyusunan rekomendaksi kebijakan pengelolaan lestari termasuk upaya konservasi. Metode utama yang digunakan adalah Manta Tow dan Reef Check. Berdasarkan skala GCRMN hasil Manta Tow diketahui bahwa keberadaan terumbu karang berkisar dari kondisi Sangat Buruk (≈12%), Buruk (≈50%), Sedang (≈13%), dan Baik (≈25%). Terumbu karang pada bagian Barat Laut serta bagian Timur tepat di dekat lokasi bertelur penyu menarik sebagai lokasi SCUBA diving dan snorkelling. Hasil Reef Check pada dua lokasi tersebut diketahui bahwa penutupan karang keras berkisar 50-60% dan dinilai tepat sebagai kawasan konservasi atau zona inti. Tanda-tanda penangkapan ikan secara destruktif dan berbagai ancaman lain terhadap ekosistem karang teramati. Penyu masih bertelur pada dua lokasi pantai, yang juga memiliki potensi eko-wisata, namun dalam kondisi meprihatinkan, memerlukan pembersihan (perawatan) dan penjagaan penyu serta telurnya dari manusia maupun hewan peliharaan terutama anjing. Pemanfaatan biota langka dan dilindungi tergolong tinggi, sehingga memerlukan peningkatan kesadaran pada semua tingkat maupun penegakan hukum. Dari aspek kesejahteraan masyarakat, kebutuhan utama adalah penyediaan air bersih. Hasil penelitian diharapkan berguna bagi masyarakat, Pemerintah Daerah Kabupaten Donggala serta stakeholders lainnya dalam perencanaan pengelolaan lestari sumberdaya pesisir Pulau Maputi.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.114
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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
Published2018
Admission routes1
Has abstractyes

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