Study of Flood Control in the Gang Mufakat of Balikpapan City (Qualitative Study)
Bibliographic record
Abstract
Balikpapan City is a city that often experiences floods. One of the most frequently flooded locations is Gang Mufakat, which is located in Damai Village, South Balikpapan. This area is an area passed by the Ampal River Basin which is one of the causes of flooding besides the lack of vegetation as land cover in the settlement. This research aims to identify the management and control/control of floods in general. This is done to obtain information on several things that are considered important in management and to assess the understanding of the community and government regarding flood control/management. The research method used is a descriptive qualitative method. This research results from the community's understanding of floods and community actions in dealing with floods. Understanding of flooding in the form of causes of flooding, and the importance of the role of vegetation on land cover and the creation of infiltration wells. The recommendation for the government is to dredge sedimentation as well as deepen the Ampal watershed, and create a polder as a substitute for water catchment areas because there are many residential areas around the Ampal watershed which do not allow water to flow directly into the watershed. The recommendation for the community is to build an infiltration well in the Gang Mufakat.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".