Model Desain Tata Ruang Kawasan Kampung Batik Celaket Berbasis Kawasan Produktif di Kota Malang
Bibliographic record
Abstract
Malang city is one leading city in tourism field that embodied concept of Tribina Cita Kota Malang where part of it is to make Malang as tourism city. Aside as a tourist destination, Malang also grows as service, trade and industrial city. By these enormous economic and trade abilities will be able to change the orientation from a tourism city into a shopping tourism city. Kampung Batik Celaket area is increasingly recognized in public eye by many physical and non physical improvements also icons creation inside Kampung Batik Celaket environment. There are five factors as design reference: factors of location, environtmental athmosphere, outdoor layout, road circulation system, and facade of buildings. These factors will be arranged into good construction in order to give comfort and safety in its shopping athmosphere.To begin with, these factors must undergo a research to understand their characteristics, so the result study can be used as a reference for planning and designing area of Kampung Batik Celaket to be one ideal, feasible and productive village.This study conducted directly on site which began from surveys, interviews, and extraction important elements through visual studies.Then, the obtainable data are tested for formulating reccommendations of designs from each subregion.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.057 | 0.007 |
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".