Analisis Kandungan Merkuri (Hg) pada Air, Sedimen, Ikan Keting (Arius caelatus), dan Ikan Mujair (Oreochromis mossambicus) di Kali Jagir Surabaya <br><i>[Analysis Of Mercury (Hg) in Water, Sediment, Keting Fish (Arius caelatus), and Mujair Fish (Oreochromis mossambicus) In Jagir River Surabaya]<i>
Bibliographic record
Abstract
Abstract Mercury (Hg) is one kind of harmful and toxic heavy metals are very harmful to the lives of both humans and other living things. Surabaya River is one of the branches of the Brantas river, in Wonokromo divided into Mas and Jagir river (Wonorejo) each lead in the Madura Strait. According Sardjono (2012) Surabaya river water was found to contain Hg which implies 100 times higher than the existing standards. The purpose of this study was to determine the levels of mercury (Hg) in water, sediment, keting fish (Arius caelatus), and mujair fish (Oreochromis mossambicus) in Jagir Surabaya river. The research method is descriptive method with sampling obtained at three stations and three replications. These results indicated that the average content of mercury (Hg) in the water of Jagir Surabaya river was at 0.0063 ppm and below threshold. The average content of mercury (Hg) in sediments Jagir Surabaya river was at 0.1433 ppm and below threshold by American standards, was above the threshold by Canadian standards. The average content of mercury (Hg) in keting fish (Arius caelatus) of Jagir Surabaya river was at 0.0096 ppm and below threshold. The average content of mercury (Hg) in mujair fish (Oreochromis mossambicus) in the Jagir Surabaya river was at 0.0112 ppm and below threshold.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".