Potensi Penurunan Debit Banjir di Sungai Sepaku Akibat Pembangunan Bendungan Sepaku Semoi
Bibliographic record
Abstract
The high rainfall in the Sepaku DAS is one of the factors causing the flooding in the River Sepaku. The heavy rain often resulted in the flooding of residents' houses and public facilities. Less water reservoirs and unavailable sustainable drainage systems are some of the causes of flooding in the region. To address the flood problems, the government plans to build a dam to control flooding and increase the need for raw water in the Penajam Paser Utara district, especially in the Sepaku district. In line with this, research has been carried out to obtain a reduction in flood discharge due to the awakening of the Sepaku Semoi Dam. This study analyzed maximum daily rainfall data from the past decade, land cover and soil types, and flood discharge using HEC-HMS with validated results. The next step is the analysis of the flood water's high surface and the dam's area using the HEC-RAS program with 2D modeling. Modeling shows that Sepaku Semoi Dam reduces flood discharge, height, and volume. Drainage was decreased by 48,450%, flood height was lowered to 0.45 m, and volume was decreased by 5,080.8 m3. The flooded area also fell by 9,144 ha.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".