Comparison of Cu Heavy Metal Concentration in Mangrove Waters and Tambak Wedi Estuary Surabaya
Bibliographic record
Abstract
The waters of the Tambak Wedi Mangrove are a stream from the Tambak Wedi Estuary in Surabaya which has the potential to be contaminated with the heavy metal Cu contained in waste from the Surabaya City area. Industrial activities and activities around the harbor as shipping traffic routes have negative impacts that trigger water pollution by the heavy metal Cu. This research aims to analyze the comparison of water quality between Mangrove Waters and Muara Tambak Wedi Surabaya based on levels of the heavy metal Cu. Water samples were taken for testing Cu levels at each of the two locations which is 5 stations. Testing for Cu heavy metal levels was carried out at the Nutrition Laboratory, Airlangga University using AAS. The results of testing for Cu heavy metal levels were analyzed descriptively and then compared with the quality standards of PP RI No. 22 of 2021. Comparison of water quality at the two locations was analyzed using the T test. The research results showed that the levels of the heavy metal Cu in Mangrove Waters ranged from 0.011-0.015 and 0.001-0.003 in Tambak Wedi Estuary Surabaya. The results of the T test analysis show a significant value of 0.00, which means there is a significant difference in the results of testing Cu levels in Mangrove Waters and Tambak Wedi Estuary Surabaya. Both waters are contaminated with the heavy metal Cu.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".