Gagasan Intervensi Lanskap dalam Meningkatkan Resiliensi terhadap Banjir di Kawasan Cagar Budaya Asia-Afrika, Kota Bandung
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Asia-Afrika colonial heritage area is facing flood proneness that is influenced by Cikapundung River hydrological problem and increasing rainfall. The study aims to examine causal process of Asia-Afrika flood phenomenon, recommend possible implementation of landscape-based solution to mainly enhance local-scale fluvial and pluvial flood resilience, and predict possible impacts of those recommendations. Water resilience concept and historical review of cultural heritage is the basis of the study, while causal process is analyzed by Driver-Pressure-State-Impact-Response (DPSIR) method. DPSIR analysis identifies that impermeable land cover around Cikapundung upstream riverbanks, embankment failure debris, lack of water absorption function, and drainage system inadequacy for surface water runoff contributes as the cause of ankle-high flood in Asia-Afrika heritage area. Landscape-based recommendations for flood control are divided into planning and design scope, which are then focused on the implementation of stormwater street systems and riparian naturalization. Provided green areas can enhance physical and psychological quality. Green-blue infrastructure as flood-controlling element can reduce the cost allocation for post-disaster handling. Green space provision, riparian space allocation, and flood control elements can lead to some consequences, such as limited public space activities and relocation of affected inhabitants, indicating the complexity of social issues in the flood problem assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it