ANALISIS KANDUNGAN LOGAM BERAT (Pb dan Cu) PADA SEDIMEN DI DAERAH ESTUARI DESA MUARA KINTAP KABUPATEN TANAH LAUT PROVINSI KALIMANTAN SELATAN
Bibliographic record
Abstract
Estuari adalah daerah pesisir semi tertutup yang menerima air tawar dari sungai dan memiliki hubungan bebas dengan laut terbuka. Aliran air sungai membawa sejumlah komponen, termasuk logam berat dalam bentuk terlarut dan partikulate. Desa Muara Kintap terdapat beragam aktivitas seperti kegiatan Pelabuhan Perikanan Muara Kintap, Stockpile, pelabuhan khusus pemuatan batu bara kedalam ponton, menyebabkan sungai muara kintap menjadi lalu lintas ponton, tugboat dan kapal nelayan, dan pada kawasan atasnya banyak aktivitas pertambangan sistem open pit di daerah Kecamatan Kintap. Aktivitas tersebut diduga menyumbang kandungan logam berat ke perairan Sungai Muara Kintap yang kemudian mengendap kedalam sedimen. Penelitian ini bertujuan untuk melihat konsentrasi logam berat Pb dan Cu pada sedimen di perairan Muara Kintap. Metode penentuan stasiun pengambilan sampel sedimen menggunakan metode Purposive sampling, logam berat dianalisis menggunakan metode AAS dan tekstur sedimen menggunakan metode pipet. Tekstur sedimen di perairan Muara Kintap pada stasiun 1, 2 dan 5 memiliki tekstur sandy mud, stasiun 3 muddy sand, stasiun 4 sand dan stasiun 6 mud. Kandungan logam berat Pb berkisar 2,036 – 11,544 mg/Kg yang berdasarkan standar baku mutu yang berlaku di Provinsi Ontario, 1993 logam berat Pb belum mengalami pencemaran. Logam berat Cu konstrasi nilainya berkisar 2,151 – 18,003 mg/Kg yang berdasarkan standar baku mutu yang berlaku di Provinsi Ontario, 1993 logam Cu melebihi standar baku mutu pada Lowest Effect Level pada level ini indikasi pencemaran sedimen masih dapat ditoleransi oleh organisme perairan.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".