Kesan antropogenik terhadap kualiti air di lembangan sungai marang, perairan Selatan Laut China Selatan
Bibliographic record
Abstract
Satu kajian kualiti air yang melibatkan pengukuran parameter seperti oksigen terlarut (DO), pH, permintaan oksigen biokimia (BOD), permintaan oksigen kimia (COD), jumlah pepejal terampai (TSS) dan nutrien terlarut telah dijalankan di lembangan Sungai Marang bermula dari bulan Julai-September 2001. Lapan stesen pensampelan telah dipilih yang merangkumi sungai utama dan cabangannya. Hasil kajian menunjukkan julat nilai untuk DO, pH, BOD, COD dan TSS masing-masing ialah 3.5-7.5 mg/L, 5.9-8.2, 0.4-1.3 mg/L, 4.0-50.2 mg/L dan 0.3-20.4 mg/L. Kepekatan ortofosfat, jumlah fosfat terlarut, nitrit, nitrat, ammonia dan jumlah nitrogen terlarut masing-masing adalah dalam julat 27-62 μg P/L, 55-105 μg P/L, 0.5-4.1 μg N/L, 65-426 μg N/L, 16-161 μg N/L dan 128-787 μg N/L. Julat kepekatan klorofil-a pula ialah 4.06-7.75 μg/L. Kajian menunjukkan taburan nutrien dipengaruhi oleh kesan antropogenik. Berdasarkan kepada Piawai Interim Kualiti Air Kebangsaan, kebanyakan kepekatan nutrien boleh dikelaskan dalam Kelas I dan II. Mengikut indeks kualiti air Jabatan Alam Sekitar, Sungai Marang berada dalam Kelas I dengan status bersih.
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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 | 0.002 | 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) | 0.045 | 0.017 |
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".