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Record W2950196546 · doi:10.33772/jsl.v4i1.6805

STRUKTUR KOMUNITAS MAKROALGA DI PERAIRAN DESA LANGARA BAJO KONAWE KEPULAUAN

2019· article· id· W2950196546 on OpenAlexaff
Nurlela Nurlela, Wa Nurgayah, Emiyarti

Bibliographic record

VenueJurnal Sapa Laut (Jurnal Ilmu Kelautan) · 2019
Typearticle
Languageid
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsLangara College
Fundersnot available
KeywordsPhysicsBiologyBotany

Abstract

fetched live from OpenAlex

Makroalga merupakan sumber daya hayati laut yang memiliki nilai ekonomis penting yang dimanfaatkan sebagai bahan makanan dan obat-obatan. Penelitian ini dilaksanakan di Perairan Desa Langara Bajo Konawe Kepulauan yang bertujuan untuk menggetahui Struktur Komunitas Makroalga, seperti indeks keanekaragaman, indeks keseragaman, indeks dominansi, dan pola sebaran makroalga. Penelitian ini dilaksanakan pada bulan April-Mei 2018, yang meliputi pengambilan data dan penggolahan data penelitian. Pengambilan data dilakukan dengan metode transek kuadrat. Pengambilan data di setiap stasiunnya dilakukan sebannyak 3 kali. Jenis makroalga yang diperoleh yaitu Halimeda opuntia, Neomeris vanbosseae, Valonia fastigiata, Dictyosphaeria cavernosa, Halimeda discoidea, Halimeda tuna, Halimeda macrobola, Ceulerpa serrulata, Chlorodesmis fastigiata, Turbinaria ornota, Dictyota bartayresiana, Padina australis, Sargassum polycystum, Amphiroa fragilissima, Glacilaria cotoni, Acanthopora spicifera, Laurencia tronai, dan Glacilaria salicornia. Indeks keanekaragaman jenis makroalga (H’) berkisar antara 0,748−2,182, indek keseragaman (E) berkisar antara 0,477−0,878, indeks dominansi (D) berkisar antara 0,144−0,581, pola sebaran (Id) berkisaran antara 0,705−2,903 termasuk kategori merata dan mengelompok. Substrat pada lokasi penelitian bertekstur pecahan karang dan pasir.Kata Kunci: Struktur Komunitas, Makroalga, Perairan Desa Langara Bajo.

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), Research integrity, 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.022

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 head0.008
GPT teacher head0.210
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; 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

Citations3
Published2019
Admission routes1
Has abstractyes

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