Application of the British Columbia Water Quality Index (BC-WQI) Method to Determine the Water Quality Status of Lake Sentani in Jayapura
Bibliographic record
Abstract
This Lake Sentani in Papua Province has significant ecological and economic value and is a source of life for the local community. However, intensive anthropogenic activities around the lake result in a decline in water quality that threatens the ecosystem and public health. This study aims to examine the water quality status of Lake Sentani using the British Columbia Water Quality Index (BC-WQI) method, which is able to integrate various physical, chemical, and biological parameters into one quality index that is easy to interpret. Data collection was carried out at three location points in the upstream, middle, and downstream parts of Lake Sentani, with in situ and ex situ testing for ten water quality parameters such as TDS, pH, BOD, COD, heavy metals Pb, oils and fats, and total coliforms. The calculation of the water quality index uses the values of F1 (scope), F2 (frequency), and F3 (amplitude) to determine the BC-WQI. The results showed that at station 1 (Ifale) the BC-WQI value was 37.62 (good quality), at station 2 (Asei) it was 49.92 (poor quality), and at station 3 (Jaifuri) it was 67.69 (poor quality). Thus, the water quality downstream of the lake is classified as unsafe for consumption or clean water without adequate treatment. This study shows the importance of integrated management and efforts to preserve water quality to maintain the sustainability of Lake Sentani.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 teacher head, 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".