PENGARUH ARUS LAUT TERHADAP SEBARAN TSS DI PERAIRAN RAROWATU UTARA KABUPATEN BOMBANA
Bibliographic record
Abstract
Penyebaran TSS di perairan pantai dan estuari dipengaruhi oleh pola arus pasang surut. Penelitian ini bertujuan untuk mengetahui bentuk pola arus, sebaran TSS dan untuk mengetahui hubungan pola arus dan sebaran TSS di Rarowatu Utara Kabupaten Bombana. Pengambilan data lapangan meliputi pengukuran arus menggunakan current meter, pengukuran pasang surut, dan pengambilan sampel air TSS. Hasil pengukuran arus yang diperoleh yaitu kecepatan arus rata-rata pada saat pengukuran di lokasi stasiun adalah 0,611 m/s dengan arah arus dominan ke arah barat laut. Kecepatan arut tertinggi terdapat pada stasiun V dengan kecepatan arus 0,111 m/s dan kecepatan arus terendah didapatkan pada stasiun IV dengan kecepatan arus yaitu 0.093 m/s. Nilai rata-rata kandungan TSS pada saat pasang yaitu 22,15 mg/l. Hasil pengukuran TSS tertinggi berada pada stasiun IV yaitu 24,6 mg/l sedangkan hasil pengukuran terendah pada stasiun III yaitu 15,4 mg/l. Sebaran TSS sangat dipengaruhi oleh pola arus dimana kecepatan arus yang tinggi dan cenderung mengarah ke barat laut menyebabkan konsentrasi sedimen tersuspensi terakumulasi di dekat dengan garis pantai dan estuari.Kata Kunci: arus, pasang surut, TSS, perairan Rarowatu Utara
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".