Analisis Kandungan Logam Timbal (Pb) pada Sedimen dan Udang Windu (Penaeus monodon) di Pantai Biringkassi Kecamatan Bungoro Kabupaten Pangkep
Bibliographic record
Abstract
Perairan Biringkassi, Kecamatan Bungoro, Kabupaten Pangkep, Sulawesi Selatan beresiko terpolusi Pb dari kegiatan bongkar-muat batubara di Pelabuhan Biringkassi dan penangkapan ikan menggunakan perahu berbahan bakar bensin. Penelitian ini bertujuan untuk mengetahui apakah sedimen dan udang windu di perairan ini telah terpolusi logam Pb. Sampel diambil di perairan sekitar Pelabuhan Biringkassi dan di sekitar pulau Camba-cambayya yang berjarak 7 km ke arah barat Pelabuhan Biringkassi dan relatif masih jauh dari keramaian kegiatan manusia. Pengukuran kadar Pb menggunakan metode spektroskopi serapan atom di laboratorium yang telah terakreditasi di Makassar. Konsentrasi Pb di sedimen perairan Biringkassi adalah 47,33 ± 11,34 mg/kg dan di sedimen perairan Pulau Camba-cambayya adalah 28,23 ± 5,17 mg/kg. Konsentrasi Pb udang windu yang ditangkap di perairan Biringkassi adalah 2,19 ± 0,98 mg/kg sedangkan yang ditangkap di sekitar Pulau Camba-cambayya adalah 0,54 ± 0,21 mg/kg. Student T-test yang digunakan untuk menentukan apakah sampel telah terpolusi logam Pb (melewati ambang batas 30,2 mg/kg untuk sedimen [Canadian Council of Ministers of the Environment, 1999] dan 0,5 mg/kg menurut Badan Pengawasan Obat dan Makanan Republik Indonesia) menunjukkan sedimen dan udang windu dari perairan Biringkassi telah terpolusi logam Pb. Kata kunci: Sedimen, Udang windu, Pb, SSA
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".