Studio Perancangan Arsitektur Kota: Kampung Wisata Hijau Organik Cilegong, Desa Mekarwangi
Bibliographic record
Abstract
The formal housing expansion by private property developers in Tangerang District has the potential to generate "urban void" due to the degradation of the quality of local informal settlements into slums. Between the rich and the poor do not have shared space, to meet and to communicate, but instead hindered by the construction of a concrete wall separating the two sides with a lame gap. Mekarwangi Village is one of the villages in Kecamatan Cisauk, Tangerang Regency, which some part of the area will be built formal housing. To overcome the negative impact, it is necessary step in integrating it with formal housing. One of them is to plan a comperhensive settlement design, but also affordable and in accordance with the local character, and promote sustainability. Community service activities are integrated along side with research into the teaching; the course Urban Design Studio. Beside lecturers and students, this activity also involved the local residents and local agencies. The scope of this case study is in one neigborhoods of Mekarwangi Village; Kampung Cilegong. How the settlement planning and design will be suitable for Kampung Cilegong? This research uses qualitative method to get deeper problem. This study aims to find a solution for Mekarwangi Village in the future. This activity is succeeded and satisfied the citizens of Kampung Cilegong, Mekarwangi Village
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.266 | 0.047 |
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".