STUDI PEMETAAN DAERAH GENANGAN BANJIR DAS SEI KAMBING DENGAN SISTEM INFORMASI GEOGRAFIS
Bibliographic record
Abstract
Sei Sikambing River Basin is one of the Sub Das of Deli River which has an important role in water requirement in Medan City. Rainfall with high intensity is supported by changes in land use causing floods which reach 0.6 m to 1 m from river banks. The purpose of this study was to map the Sei Kambing River basin flood inundation area as information to the public in disaster mitigation efforts. The scope of this research is to analyze the maximum daily rainfall with a return period of 2 to 100 years, analyze flood discharge with a return period of 2 to 100, analyze flood water levels with HECRAS software, and spatially map flood inundation areas with GIS. The results showed that the return flood rate of the Sikambing watershed with a 25-year return period of 211.94 m3/s caused the flood level of the Sikambing watershed to be between 1.7 m to 3.7 m. The Sikambing watershed flood inundation area reached an area of 1.19 Km2 which resulted in the impact of flooding on 5 sub-districts in Medan, namely Medan Selayang District, Medan Sunggal, Medan Petisah, Medan Helvetia, and West Medan.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".