ANALISIS KUALITAS AIR SUNGAI BALANGAN DI KABUPATEN BALANGAN BERDASARKAN PARAMETER FISIK DAN KIMIA (LOGAM TERLARUT)
Bibliographic record
Abstract
The Balangan River stretches and flows in the Balangan Regency area. Balangan River length is 30 Km, has a width of about 50 m wide and average depth of 3.5 m. The Balangan River flows through 8 districts (Paringin District, Paringin Selatan District, Lampihong District, Batumandi District, Awayan District, Tebing Tinggi District, Juai District and Halong District). The Balangan River is used by the local community as a source of clean water for household needs (bath wash toilet), agriculture and farming. Further and more specific research on the water quality of the Balangan River is urgently needed to obtain information regarding the status of water quality, water quality status and obtain pollutant load information as well as to be evaluated so that it can be used as a recommendation for efforts to reduce pollutant loads so that the target of improving water quality is well achieved by the community and local government. This study aims to identify the water quality of the Balangan River based on physical and chemical parameters. Data collection was carried out in the measurement range of the first quarter of 2015 to the third quarter of 2022 by taking river water samples every quarter. Sampling points and inspection of the insitu water quality of the Balangan River were carried out at two locations in the upstream and downstream. The surface water sampling method used is in accordance with SNI 6989.57:2008. During the measurement period in the Balangan River, physical and chemical parameters that did not meet the quality standards required in Government Regulation no. 22 of 2021 attachment VI (Class 1) are Total Suspended Solid (TSS), Iron (Fe) and Zinc (Zn).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".