STRUKTUR KOMUNITAS MAKROALGA DI PERAIRAN DESA LANGARA BAJO KONAWE KEPULAUAN
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".